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Implementation of RPA technology involves the deployment of software robots that execute recurring clerical tasks; bots are complemented with AI can streamline even more complex activities. Businesses are adopting RPA at an increased pace: the 2024 forecast from Precedence Research states that the RPA market, which has reached $18.41 billion in 2023, will grow at a CAGR of 25.7% from 2024 to 2033.

What lies behind the increasing popularity of RPA among industries? By adopting the technology, companies can reap numerous RPA benefits, and the most notable one is reduced operational cost. As an example, 52% of financial services organizations surveyed by SMA Technologies in 2024 stated automation helps them save at least $100,000 annually.

This article explores how RPA enables companies to reduce their business costs.

Streamlining Workforce Productivity

Companies spend vast financial resources on human labor. Among all cost factors (recruiting and training costs, payroll taxes, etc.), employee compensation takes up the greatest share. The average compensation cost for private sector workers reached $43.78 per hour by March 2024, as stated by the Bureau of Labor Statistics, and this figure is even higher in the public area. Therefore, even one employee can cost over $100,000 per year.

Unfortunately, employees have to spend many paid work hours on clerical tasks, which don’t considerably impact a company’s bottom line. Thus, many of these and other labor costs do not pay off. The recent Slack Workforce Index shows that, on average, employees spend at least a third of their workdays on activities they consider low-value.

Companies can solve this challenge by implementing RPA bots and delegating a wide range of repetitive and time-consuming tasks to them. These can involve rule-based activities, including data input or extraction, and even high-value tasks, such as customer communication or fraud detection if bots are complemented with AI.

Raben Group, a Dutch-based logistics services provider, manages 1.6 million square meters of warehouse space and 12,000 employees globally. The company has deployed over 200 RPA automations to optimize multiple processes, including the generation of spot offers for customers. In one year, automation has saved the company 78,815 employee workdays and over €6 million.

Enhancing Data Quality

More than 50% of respondents to the 2023 survey commissioned by Monte Carlo Data believe that data quality issues negatively affect a quarter or even a more significant part of their revenues. According to the same study, companies can lose $3 for every $10 in revenue due to poor data quality.

A company can implement RPA bots to automate manual error-prone processes, such as data entry and output, thereby reducing the number of data errors. In the long run, the implementation of RPA allows companies to improve their data’s accuracy, relevance, and reliability and avoid expenses related to poor data quality.

Companies can further improve data quality by applying specific data processing rules to their automation scenarios. For example, a bot can be programmed to check and validate the data it works with in order to identify missing and duplicate data. If the bot discovers data issues, it can flag the affected data set and thus signal a human worker to check it.

Numerous real-life implementation examples prove the positive effect of RPA on data quality. For instance, Siemens deployed an AI-powered bot to detect and fix incorrect tax codes among its purchase orders. The bot helped the company mitigate manual tax code checks and achieve 95% tax code accuracy, which resulted in enhanced procurement efficiency.

Ensuring Regulatory Compliance

A company that cannot ensure the compliance of its work processes with global or industry-specific standards risks losing its business reputation and getting a large fine from regulators. Fortunately, companies can overcome regulatory compliance challenges by implementing RPA technology.

A bot can automatically collect financial records required for an internal financial audit across various repositories and merge data from these records into a single dataset to simplify further analysis. By assisting auditors with this monotonous and exhausting task, bots allow human specialists to focus on their direct duties, namely identifying discrepancies in financial documents.

In addition, the bot can automate KYC and AML processes and help a company ensure compliance with FINRA requirements. For example, a bank can implement an AI-powered bot to conduct comprehensive checks of client data before providing financial services. It can automatically scan documents, extract relevant client data, and compare it with government or corporate databases to identify and flag discrepancies.

HBL, Pakistan’s largest bank with over 1,700 branches and 37 million customers worldwide, has deployed over 100 RPA automations in recent years. The bank has automated a wide range of processes, including sanction screening for new customers. The automation has helped the bank achieve a 98% accuracy of sanction screening checks while saving 341,000 working hours annually.

Improving Cybersecurity

Data breaches are becoming highly costly to businesses. IBM’s recent report revealed that by 2024, the average cost of a data breach reached $4.88 million globally.

Companies can avoid these devastating financial losses by implementing RPA bots that are complemented with AI capabilities. The same IBM’s report states that companies using automation and AI in cybersecurity can save an average of $2.22 million annually.

There are multiple use cases for RPA in cybersecurity. For instance, AI-enabled bots can monitor user transactions and interactions in different software systems and detect any anomalies to identify cyber threats in real time. These can include fraudulent transactions, compromised user accounts, or DDoS attacks.

If a bot discovers a security incident, it can automatically take simple actions as an initial response. For example, if a bot detects a file infected with malware in a company’s data storage, it can swiftly quarantine it and alert the security team about the incident.

Depository Trust and Clearing Corporation (DTCC), an American financial services organization, implemented RPA to manage cyber risk more efficiently. After the implementation, the company reported numerous cybersecurity improvements, including 80% quicker discovery of intrusion events and 96% faster detection of malicious URLs.

Final Thoughts

RPA technology enables companies to automate a wide range of tasks and thus become more cost-effective. Enhanced employee performance, data quality, regulatory compliance, and cybersecurity are the key outcomes of RPA adoption that lead to the optimization of business costs.

To maximize technology adoption ROI and propel its cost-saving impact, a company can consult with third-party experts before starting its RPA initiative. An experienced RPA consultant will help define the right implementation approach, deliver an adoption roadmap, and build a future-proof, easy-to-scale RPA solution.

The post How RPA Helps Reduce Business Costs appeared first on Home Business Magazine.

Original source: https://homebusinessmag.com/growing-a-business/upgrading-equipment/how-rpa-technology-reduce-business-costs/

Are you facing debt with a long-term illness and wondering how you’ll manage your money? Ongoing health issues often mean you end up dealing with unpredictable expenses like travelling to appointments, hospital parking, and prescription charges.

It can be challenging both mentally and physically, and can lead to more stress when you’re already feeling the pressure. These financial extras, as well as time off work and a reduced income, can make falling into debt more likely.

If you’re dealing with a long-term illness and are worried about debt, read our advice on what you can do to deal with your financial situation.

• Look at how you can manage your finances
• Check your statutory sick pay entitlement
• Use smart ways to reduce your spending
• Claim an income tax refund
• Consider ways to increase your income
• Try reducing your rent or mortgage payments
• Get free advice to deal with debt with a long-term illness

 

Look at how you can manage your finances

Create a simple budget to make sure your essential living expenses and care costs are taken into account. You can use our free budget template to get started.

Your budget will help you manage your incomings against your outgoings, so you can concentrate on your health instead of worrying about money. It’s also a good way to discover where you could benefit from saving cash.

 

Check your Statutory Sick Pay entitlement

Some people don’t know that you can get Statutory Sick Pay (SSP) for up to 28 weeks if:

• You’re in work, but can’t attend because you’re ill
• You were earning an average of at least £123 per week or more in the two months before you couldn’t work

That means you’ll still get paid a specified amount while you’re off work, paid into your bank account the same way you would usually get your wages.

The current entitlement is £116.75 per week for up to 28 weeks. If you’re struggling to keep up with bills or repayments while off work, this kind of entitlement could ease some of the pressure.

Some employers have their own sick pay schemes, so double check with your HR department what you’re entitled to. If you don’t have an HR department, ask your manager, or check your contract.

 

Use smart ways to reduce your spending

Even if you’re already on a tight budget, there are loads of ways you can cut back and save smartly. Use an Ofgem approved switching service to find better deals on your utility bills, look out for free evening and weekend call offers from your phone provider, and find out how to save money on your TV packages.

When it comes to your food shop, you could switch to own brand products or start shopping at a better value supermarket. Cheaper food doesn’t mean losing out on taste!

 

Claim an income tax refund

If you’ve had to stop working due to long-term illness, or have reduced hours because of it, you might be able to get a refund of some of the income tax you’ve paid.

It’s worth contacting HMRC to check if you’re entitled to some money back.

 

Consider ways to increase your income

We’re not talking about getting another job or going back to work when you’re not ready, because your health must come first. If you’re off work long-term because of your illness, or have a low income as a result, there may be some benefits you’re entitled to.

Use the StepChange benefits calculator to check what you could be missing, and look into any pensions, savings or investments you might have. This’ll help to make sure you’ve got as much money coming in as possible.

 

Try reducing your rent or mortgage payments

If you’re on a low income and renting, you can apply for a council tax discount. If you’ve got a mortgage, contact your lender or insurance provider to see if you have insurance in place that covers your payments while you’re ill.

You might have mortgage payment protection, critical illness cover, or income protection insurance to help you cover payments. However, bear in mind that any insurance pay-out could affect state benefit claims you make.

 

Get free advice to deal with debt

If you’re struggling to pay your bills, use the Stepchange online Debt Remedy tool here for advice and practical solutions to deal with your debt, or give their advisors a call.

They will talk through your finances and give you free and impartial debt advice, as well as recommend a debt solution tailored to your situation.

Also, sign up to our free debt help emails here. They will support you as you work to pay off your debts and get better.

 

Sign Up – Newsletter

The post How to deal with debt with a long-term illness appeared first on MoneyMagpie.

Original source: https://www.moneymagpie.com/make-money/how-to-deal-with-debt-with-a-long-term-illness

Google Ads will phase out the option to use enhanced cost-per-click (eCPC) for new Search and Display campaigns starting in October. 

Key dates:

• October: eCPC option removed for new campaigns.
• March 2025: All remaining eCPC campaigns transitioned to Manual CPC.

Why we care. ECPC is the most light touch of automated bid strategies, so it allowed you to dip your toe into automated bidding without giving Google full control by just working toward a conversion target. Google is taking that away. If you haven’t started testing which fully automated bid strategies work for your campaigns, now is the time. This change will impact how you manage your Search and Display campaigns.

Options. Google introduced enhanced CPC in 2010 as a Smart Bidding strategy to optimize bids based on conversion likelihood. However, newer machine learning options like Maximize conversions (with optional target CPA) and Maximize conversion value (with optional target ROAS) offer more automated tools to improve performance.

First seen. Anthony Higman shared the email he received from Google about this update on X.

Zoom out. The shift to more advanced automated bidding strategies signals Google’s push toward greater reliance on machine learning and possible introduction of more automated bidding strategies.

• Google deprecated eCPC for Shopping campaigns last year.

Original source: https://searchengineland.com/google-ads-deprecate-enhanced-cpc-search-display-446350

Are you facing debt with a long-term illness and wondering how you’ll manage your money? Ongoing health issues often mean you end up dealing with unpredictable expenses like travelling to appointments, hospital parking, and prescription charges.

It can be challenging both mentally and physically, and can lead to more stress when you’re already feeling the pressure. These financial extras, as well as time off work and a reduced income, can make falling into debt more likely.

If you’re dealing with a long-term illness and are worried about debt, read our advice on what you can do to deal with your financial situation.

• Look at how you can manage your finances
• Check your statutory sick pay entitlement
• Use smart ways to reduce your spending
• Claim an income tax refund
• Consider ways to increase your income
• Try reducing your rent or mortgage payments
• Get free advice to deal with debt with a long-term illness

 

Look at how you can manage your finances

Create a simple budget to make sure your essential living expenses and care costs are taken into account. You can use our free budget template to get started.

Your budget will help you manage your incomings against your outgoings, so you can concentrate on your health instead of worrying about money. It’s also a good way to discover where you could benefit from saving cash.

 

Check your Statutory Sick Pay entitlement

Some people don’t know that you can get Statutory Sick Pay (SSP) for up to 28 weeks if:

• You’re in work, but can’t attend because you’re ill
• You were earning an average of at least £123 per week or more in the two months before you couldn’t work

That means you’ll still get paid a specified amount while you’re off work, paid into your bank account the same way you would usually get your wages.

The current entitlement is £116.75 per week for up to 28 weeks. If you’re struggling to keep up with bills or repayments while off work, this kind of entitlement could ease some of the pressure.

Some employers have their own sick pay schemes, so double check with your HR department what you’re entitled to. If you don’t have an HR department, ask your manager, or check your contract.

 

Use smart ways to reduce your spending

Even if you’re already on a tight budget, there are loads of ways you can cut back and save smartly. Use an Ofgem approved switching service to find better deals on your utility bills, look out for free evening and weekend call offers from your phone provider, and find out how to save money on your TV packages.

When it comes to your food shop, you could switch to own brand products or start shopping at a better value supermarket. Cheaper food doesn’t mean losing out on taste!

 

Claim an income tax refund

If you’ve had to stop working due to long-term illness, or have reduced hours because of it, you might be able to get a refund of some of the income tax you’ve paid.

It’s worth contacting HMRC to check if you’re entitled to some money back.

 

Consider ways to increase your income

We’re not talking about getting another job or going back to work when you’re not ready, because your health must come first. If you’re off work long-term because of your illness, or have a low income as a result, there may be some benefits you’re entitled to.

Use the StepChange benefits calculator to check what you could be missing, and look into any pensions, savings or investments you might have. This’ll help to make sure you’ve got as much money coming in as possible.

 

Try reducing your rent or mortgage payments

If you’re on a low income and renting, you can apply for a council tax discount. If you’ve got a mortgage, contact your lender or insurance provider to see if you have insurance in place that covers your payments while you’re ill.

You might have mortgage payment protection, critical illness cover, or income protection insurance to help you cover payments. However, bear in mind that any insurance pay-out could affect state benefit claims you make.

 

Get free advice to deal with debt

If you’re struggling to pay your bills, use the Stepchange online Debt Remedy tool here for advice and practical solutions to deal with your debt, or give their advisors a call.

They will talk through your finances and give you free and impartial debt advice, as well as recommend a debt solution tailored to your situation.

Also, sign up to our free debt help emails here. They will support you as you work to pay off your debts and get better.

 

Sign Up – Newsletter

The post How to deal with debt with a long-term illness appeared first on MoneyMagpie.

Original source: https://www.moneymagpie.com/make-money/how-to-deal-with-debt-with-a-long-term-illness

Are you facing debt with a long-term illness and wondering how you’ll manage your money? Ongoing health issues often mean you end up dealing with unpredictable expenses like travelling to appointments, hospital parking, and prescription charges.

It can be challenging both mentally and physically, and can lead to more stress when you’re already feeling the pressure. These financial extras, as well as time off work and a reduced income, can make falling into debt more likely.

If you’re dealing with a long-term illness and are worried about debt, read our advice on what you can do to deal with your financial situation.

• Look at how you can manage your finances
• Check your statutory sick pay entitlement
• Use smart ways to reduce your spending
• Claim an income tax refund
• Consider ways to increase your income
• Try reducing your rent or mortgage payments
• Get free advice to deal with debt with a long-term illness

 

Look at how you can manage your finances

Create a simple budget to make sure your essential living expenses and care costs are taken into account. You can use our free budget template to get started.

Your budget will help you manage your incomings against your outgoings, so you can concentrate on your health instead of worrying about money. It’s also a good way to discover where you could benefit from saving cash.

 

Check your Statutory Sick Pay entitlement

Some people don’t know that you can get Statutory Sick Pay (SSP) for up to 28 weeks if:

• You’re in work, but can’t attend because you’re ill
• You were earning an average of at least £123 per week or more in the two months before you couldn’t work

That means you’ll still get paid a specified amount while you’re off work, paid into your bank account the same way you would usually get your wages.

The current entitlement is £116.75 per week for up to 28 weeks. If you’re struggling to keep up with bills or repayments while off work, this kind of entitlement could ease some of the pressure.

Some employers have their own sick pay schemes, so double check with your HR department what you’re entitled to. If you don’t have an HR department, ask your manager, or check your contract.

 

Use smart ways to reduce your spending

Even if you’re already on a tight budget, there are loads of ways you can cut back and save smartly. Use an Ofgem approved switching service to find better deals on your utility bills, look out for free evening and weekend call offers from your phone provider, and find out how to save money on your TV packages.

When it comes to your food shop, you could switch to own brand products or start shopping at a better value supermarket. Cheaper food doesn’t mean losing out on taste!

 

Claim an income tax refund

If you’ve had to stop working due to long-term illness, or have reduced hours because of it, you might be able to get a refund of some of the income tax you’ve paid.

It’s worth contacting HMRC to check if you’re entitled to some money back.

 

Consider ways to increase your income

We’re not talking about getting another job or going back to work when you’re not ready, because your health must come first. If you’re off work long-term because of your illness, or have a low income as a result, there may be some benefits you’re entitled to.

Use the StepChange benefits calculator to check what you could be missing, and look into any pensions, savings or investments you might have. This’ll help to make sure you’ve got as much money coming in as possible.

 

Try reducing your rent or mortgage payments

If you’re on a low income and renting, you can apply for a council tax discount. If you’ve got a mortgage, contact your lender or insurance provider to see if you have insurance in place that covers your payments while you’re ill.

You might have mortgage payment protection, critical illness cover, or income protection insurance to help you cover payments. However, bear in mind that any insurance pay-out could affect state benefit claims you make.

 

Get free advice to deal with debt

If you’re struggling to pay your bills, use the Stepchange online Debt Remedy tool here for advice and practical solutions to deal with your debt, or give their advisors a call.

They will talk through your finances and give you free and impartial debt advice, as well as recommend a debt solution tailored to your situation.

Also, sign up to our free debt help emails here. They will support you as you work to pay off your debts and get better.

 

Sign Up – Newsletter

The post How to deal with debt with a long-term illness appeared first on MoneyMagpie.

Original source: https://www.moneymagpie.com/make-money/how-to-deal-with-debt-with-a-long-term-illness

Are you facing debt with a long-term illness and wondering how you’ll manage your money? Ongoing health issues often mean you end up dealing with unpredictable expenses like travelling to appointments, hospital parking, and prescription charges.

It can be challenging both mentally and physically, and can lead to more stress when you’re already feeling the pressure. These financial extras, as well as time off work and a reduced income, can make falling into debt more likely.

If you’re dealing with a long-term illness and are worried about debt, read our advice on what you can do to deal with your financial situation.

• Look at how you can manage your finances
• Check your statutory sick pay entitlement
• Use smart ways to reduce your spending
• Claim an income tax refund
• Consider ways to increase your income
• Try reducing your rent or mortgage payments
• Get free advice to deal with debt with a long-term illness

 

Look at how you can manage your finances

Create a simple budget to make sure your essential living expenses and care costs are taken into account. You can use our free budget template to get started.

Your budget will help you manage your incomings against your outgoings, so you can concentrate on your health instead of worrying about money. It’s also a good way to discover where you could benefit from saving cash.

 

Check your Statutory Sick Pay entitlement

Some people don’t know that you can get Statutory Sick Pay (SSP) for up to 28 weeks if:

• You’re in work, but can’t attend because you’re ill
• You were earning an average of at least £123 per week or more in the two months before you couldn’t work

That means you’ll still get paid a specified amount while you’re off work, paid into your bank account the same way you would usually get your wages.

The current entitlement is £116.75 per week for up to 28 weeks. If you’re struggling to keep up with bills or repayments while off work, this kind of entitlement could ease some of the pressure.

Some employers have their own sick pay schemes, so double check with your HR department what you’re entitled to. If you don’t have an HR department, ask your manager, or check your contract.

 

Use smart ways to reduce your spending

Even if you’re already on a tight budget, there are loads of ways you can cut back and save smartly. Use an Ofgem approved switching service to find better deals on your utility bills, look out for free evening and weekend call offers from your phone provider, and find out how to save money on your TV packages.

When it comes to your food shop, you could switch to own brand products or start shopping at a better value supermarket. Cheaper food doesn’t mean losing out on taste!

 

Claim an income tax refund

If you’ve had to stop working due to long-term illness, or have reduced hours because of it, you might be able to get a refund of some of the income tax you’ve paid.

It’s worth contacting HMRC to check if you’re entitled to some money back.

 

Consider ways to increase your income

We’re not talking about getting another job or going back to work when you’re not ready, because your health must come first. If you’re off work long-term because of your illness, or have a low income as a result, there may be some benefits you’re entitled to.

Use the StepChange benefits calculator to check what you could be missing, and look into any pensions, savings or investments you might have. This’ll help to make sure you’ve got as much money coming in as possible.

 

Try reducing your rent or mortgage payments

If you’re on a low income and renting, you can apply for a council tax discount. If you’ve got a mortgage, contact your lender or insurance provider to see if you have insurance in place that covers your payments while you’re ill.

You might have mortgage payment protection, critical illness cover, or income protection insurance to help you cover payments. However, bear in mind that any insurance pay-out could affect state benefit claims you make.

 

Get free advice to deal with debt

If you’re struggling to pay your bills, use the Stepchange online Debt Remedy tool here for advice and practical solutions to deal with your debt, or give their advisors a call.

They will talk through your finances and give you free and impartial debt advice, as well as recommend a debt solution tailored to your situation.

Also, sign up to our free debt help emails here. They will support you as you work to pay off your debts and get better.

 

Sign Up – Newsletter

The post How to deal with debt with a long-term illness appeared first on MoneyMagpie.

Original source: https://www.moneymagpie.com/make-money/how-to-deal-with-debt-with-a-long-term-illness

Are you facing debt with a long-term illness and wondering how you’ll manage your money? Ongoing health issues often mean you end up dealing with unpredictable expenses like travelling to appointments, hospital parking, and prescription charges.

It can be challenging both mentally and physically, and can lead to more stress when you’re already feeling the pressure. These financial extras, as well as time off work and a reduced income, can make falling into debt more likely.

If you’re dealing with a long-term illness and are worried about debt, read our advice on what you can do to deal with your financial situation.

• Look at how you can manage your finances
• Check your statutory sick pay entitlement
• Use smart ways to reduce your spending
• Claim an income tax refund
• Consider ways to increase your income
• Try reducing your rent or mortgage payments
• Get free advice to deal with debt with a long-term illness

 

Look at how you can manage your finances

Create a simple budget to make sure your essential living expenses and care costs are taken into account. You can use our free budget template to get started.

Your budget will help you manage your incomings against your outgoings, so you can concentrate on your health instead of worrying about money. It’s also a good way to discover where you could benefit from saving cash.

 

Check your Statutory Sick Pay entitlement

Some people don’t know that you can get Statutory Sick Pay (SSP) for up to 28 weeks if:

• You’re in work, but can’t attend because you’re ill
• You were earning an average of at least £123 per week or more in the two months before you couldn’t work

That means you’ll still get paid a specified amount while you’re off work, paid into your bank account the same way you would usually get your wages.

The current entitlement is £116.75 per week for up to 28 weeks. If you’re struggling to keep up with bills or repayments while off work, this kind of entitlement could ease some of the pressure.

Some employers have their own sick pay schemes, so double check with your HR department what you’re entitled to. If you don’t have an HR department, ask your manager, or check your contract.

 

Use smart ways to reduce your spending

Even if you’re already on a tight budget, there are loads of ways you can cut back and save smartly. Use an Ofgem approved switching service to find better deals on your utility bills, look out for free evening and weekend call offers from your phone provider, and find out how to save money on your TV packages.

When it comes to your food shop, you could switch to own brand products or start shopping at a better value supermarket. Cheaper food doesn’t mean losing out on taste!

 

Claim an income tax refund

If you’ve had to stop working due to long-term illness, or have reduced hours because of it, you might be able to get a refund of some of the income tax you’ve paid.

It’s worth contacting HMRC to check if you’re entitled to some money back.

 

Consider ways to increase your income

We’re not talking about getting another job or going back to work when you’re not ready, because your health must come first. If you’re off work long-term because of your illness, or have a low income as a result, there may be some benefits you’re entitled to.

Use the StepChange benefits calculator to check what you could be missing, and look into any pensions, savings or investments you might have. This’ll help to make sure you’ve got as much money coming in as possible.

 

Try reducing your rent or mortgage payments

If you’re on a low income and renting, you can apply for a council tax discount. If you’ve got a mortgage, contact your lender or insurance provider to see if you have insurance in place that covers your payments while you’re ill.

You might have mortgage payment protection, critical illness cover, or income protection insurance to help you cover payments. However, bear in mind that any insurance pay-out could affect state benefit claims you make.

 

Get free advice to deal with debt

If you’re struggling to pay your bills, use the Stepchange online Debt Remedy tool here for advice and practical solutions to deal with your debt, or give their advisors a call.

They will talk through your finances and give you free and impartial debt advice, as well as recommend a debt solution tailored to your situation.

Also, sign up to our free debt help emails here. They will support you as you work to pay off your debts and get better.

 

Sign Up – Newsletter

The post How to deal with debt with a long-term illness appeared first on MoneyMagpie.

Original source: https://www.moneymagpie.com/make-money/how-to-deal-with-debt-with-a-long-term-illness

AI winter is a term that describes funding cuts in research and development of artificial intelligence systems. 

This usually follows after a period of overhype and under-delivery in the expectations of AI systems capabilities. Does this sound like today’s AI? 

Over the past few months, we’ve observed several key generative AI systems failing to meet the promise of investors and Silicon Valley executives – from the recent launch of Open AI’s GPT-4o model to Google’s AI Overviews to Perspective’s plagiarism engine and a ton more.

While such periods are typically temporary, they can impact the industry’s growth. 

This article tackles:

• A brief history of AI winters and the reasons each one occurred.
• Characteristics and lessons learned from past AI winters.
• Are we headed for an AI winter now?
• The future of AI in search and your role in it.

Brief history of AI winters and the reasons each one occurred

The field of AI has a rich (albeit quite short) history, marked by periods of intense excitement followed by somewhat of a disappointment. These periods of decline are what we now call AI winters.

The first one occurred in the 1970s. Early AI projects like machine translation and speech recognition failed to meet the ambitious expectations set for them. Funding for AI research dried up, leading to a slowdown in progress. 

Several factors contributed to the first AI winter. 

In a nutshell, researchers over-promised the capabilities of what AI could achieve in the short term. 

Even now, we don’t fully understand human intelligence, making it hard to replicate in AI.

Another key factor was that the computing power available at the time was insufficient to handle the growing demands of the AI field, which inevitably halted progress in the area. 

Some progress was observed in the 1980s with the development of expert systems, which successfully solved specific problems in limited domains. This period of excitement lasted until the late 1980s and early 1990s when another AI winter arrived.

This time, the reasons were more closely related to the death of one computing technology – the LISP machine, which was replaced by more efficient alternatives. 

Simultaneously, expert systems failed to meet expectations when prompted with unexpected inputs, leading to errors and erosion of trust. 

One key effort in replacing the LISP machines was the Japanese Fifth Generation project.

This was a collaboration between the country’s computing industry and government that aimed to revolutionize AI operating systems and computing techniques, technologies and hardware. It ultimately failed to meet most of its goals.  

Despite research in AI continuing throughout the 1990s, many researchers avoided using the term “AI” to distance themselves from the field’s history of failed promises. 

This is quite similar to a trend observed at the moment, with many prominent researchers carefully signifying the specific area of research they are operating in and avoiding using the umbrella term. 

AI interest grew in the early 2000s due to machine learning and computing advances, but practical integration was slow.

Despite this period being referred to as the “AI spring,” the term “AI” itself remained tarnished by past failures and unmet expectations. 

Investors and researchers alike shied away from the term, associating it with overhyped and underperforming systems. 

As a result, AI was often rebranded under different names, such as machine learning, informatics or cognitive systems. This allowed researchers to distance themselves from the stigma associated with AI and secure funding for their work.

From 2000 to 2020, IBM’s Watson was a prime example of the failed integration of AI, following the company’s promise to revolutionize healthcare and diagnostics. 

Despite its success on the game show Jeopardy!, the AI super project faced significant challenges when applied to real-world healthcare. 

The Oncology Expert Advisor, in collaboration with the MD Anderson Cancer Center, struggled to interpret doctors’ notes and apply research findings to individual patient cases. 

A similar project at Memorial Sloan Kettering Cancer Center encountered problems due to the use of synthetic data, which introduced bias and failed to account for real-world variations in patient cases and treatment options. 

When Watson was implemented in other parts of the world, its recommendations were often irrelevant or incompatible with local healthcare infrastructures and treatment regimens. 

Even in the U.S., it was criticized for providing obvious or impractical advice. 

Ultimately, Watson’s failure in healthcare highlights the challenges of applying AI to complex, real-world problems and the importance of considering context and data limitations.

Meanwhile, several AI-related trends emerged. These niche technologies gained buzz and funding but quickly faded after failing to live up to the hype.

Think of:

• Chatbots. 
• IoT (internet of things).
• Voice-command devices.
• Big data.
• Blockchain.
• Augmented reality.
• Autonomous vehicles. 

All of these areas of research and development still have a ton of potential, but investor interest has peaked at separate periods in the past. 

Overall, the history of AI is a cautionary tale of the dangers of hype and unrealistic expectations, despite also demonstrating the resilience and progress of the industry’s mission. Despite the setbacks, AI technologies have evolved. 

Dig deeper: No, AI won’t change your marketing job: A contrarian perspective

Characteristics and lessons learned from past AI winters

Generative AI is the most recent iteration in the cycle of AI breakthrough, hype, investment and multi-faceted technology integration in many areas of life and business. 

Let’s track whether it is currently headed toward an AI winter. But before that, allow me to briefly recap the lessons learned from each past AI winter. 

Each AI winter shares the following key milestones: 

Hype cycle

• AI winters often follow periods of intense hype and inflated expectations.
• The gap between these unrealistic expectations and the actual capabilities of AI technology leads to disappointment and disillusionment.

Technical barriers

• AI winters frequently coincide with technical limitations.
• Whether it’s a lack of computational power, algorithmic challenges or insufficient data, these barriers can significantly impede progress.

Financial drought

• As enthusiasm for AI wanes, funding for research and development dries up.
• This lack of investment can further stifle innovation and exacerbate the slowdown.

Backlash and skepticism

• AI winters often witness a surge in criticism and skepticism from both the scientific community and the public.
• This negative sentiment can further dampen the mood and make it difficult to secure funding or support.

Strategic retreat

• In response to these challenges, AI researchers often shift their focus to more manageable, less ambitious projects.
• This can involve rebranding their work or focusing on specific applications to avoid the negative connotations associated with AI.
• Then a niche breakthrough occurs, starting the cycle all over again.

AI winters aren’t just a temporary setback; they can really hurt progress.

Funding dries up, projects get abandoned and talented people leave the field. This means we miss out on potentially life-changing technologies.

Plus, AI winters can make people suspicious of AI, making it harder for even good AI to be accepted.

Since AI is becoming increasingly integrated into our countries’ economies, our lives and many businesses, a downturn hurts everyone.

It’s like hitting the brakes just as we start making progress toward achieving some of the world’s biggest tech-related goals like AGI (artificial general intelligence).

These cycles also discourage long-term research, leading to a focus on short-term gains.

Despite stalling progress, AI winters offer valuable learning experiences. They remind us to be realistic about AI’s capabilities, focus on foundational research and ensure diverse funding sources.

Collaboration across different sectors is key, as is transparent communication about AI’s potential and limitations – especially to investors and the public.

By embracing these lessons, we can create a sustainable and impactful future for AI that truly benefits society.

Let’s address the big question – are we currently headed toward an AI winter?

---

Are we headed for an AI winter now? 

It appears that progress in AI has slowed down a bit after an explosive 2023, both with regard to new technologies released, updates to existing models and hype around generative AI.

People like Gary Marcus believe that the big leaps forward in AI model performance are becoming less frequent.

The lack of breakthroughs in generative AI and new model developments from the leaders in the space suggests a potential slowdown in progress.

Judging by investor calls, mentions of AI have also decreased, leading more to believe that the productivity gains that generative AI promised would not manifest more than what has already been achieved.

Admittedly, it isn’t much. The ROI isn’t great. Many companies struggle to find the productivity returns expected from their AI investments.

The rapid advancements and excitement around tools like ChatGPT have inflated expectations about their capabilities and potential impact.

Something previously apparent to only a small fraction of the population, mostly AI researchers, is now becoming general knowledge – large language models (LLMs).

These models face major limitations, including hallucinations and a lack of true understanding, which reduces their practical impact.

People are realizing that these technologies, when misused, are already harming the web. AI-generated content has spread across the web, from social media comments to posts, blogs, videos and podcasts.

Authentic human-generated content is becoming scarce. Future AI models will inevitably be trained on synthetic content, making it impossible to avoid and leading to worse performance over time.

We haven’t even addressed the ease of hacking generative AI, ethical issues in sourcing training data, challenges in protecting user data and many other problems that tech companies often overlook in AI discussions.

Still, some signs point against an impending AI winter in the short term.

AI technology continues to evolve rapidly, with open-source models rapidly catching up to closed models and innovative applications like AI agents emerging.

Furthermore, AI is being integrated into various industries and applications, often seamlessly (sometimes not – looking at you, AI Overviews), demonstrating at least some practical value.

It’s unclear whether these implementations will meet the tests of time.

Ongoing investment in companies like Perplexity shows investors’ confidence in AI’s potential for search, despite skeptics debunking some of the company’s claims and questioning its tactics around intellectual property.

Dig deeper: Google AI Overviews are an evolution, not a revolution

The future of AI in search and your role in it

AI is undoubtedly here to stay. My fellow automation enthusiasts and I are thrilled that everyone is now excited about this technology and exploring it themselves.

It’s important not to let the current excitement raise your expectations too high. The technology still has limits and a long way to go before reaching its full potential.

Beware of tech bros and CEOs promising uncanny ROI or sharing their doomsday predictions of the day (always so, so soon) where there will be AGI and you will be replaced by AI. 

While automation is revolutionizing the workforce, change is gradual. 

Progress is being made toward AGI, but reputable AI researchers believe this reality will not come in the immediate future. Numerous obstacles must still be overcome to achieve this. 

Understanding any emerging technologies (especially those so widely discussed as AI is at the moment) and how they work is crucial to creating strategies that stand the test of time. 

What we might see happening (in search, in particular) is one of two scenarios. 

Progress continues

Implementations stand the test of time, and models improve. 

For search marketers, this might mean more AI-generated content to outcompete but also improved search systems and AI-detection algorithms, easing this task by amplifying human-written, authentic voices. 

Investors win. Big tech wins. Everyone wins. 

That is if we solve the challenges related to ethics, security, IP and resource use. But I digress.

Progress stalls

Systems become worse. Think:

• No improvement in Google AI Overviews.
• Even more spam in web results.
• Misinformation.
• Entirely poisoned social media feeds, online forums and other digital spaces. 

In this scenario, big tech will start bleeding money rapidly. (Some evidence suggests this trend has already begun.) 

AI systems are, at the end of the day, expensive to develop, maintain and improve. 

Failing to do so, however, will tarnish investor trust and they will eventually bow down to scaling back implementations in the area. 

The public failure of several of these technologies to meet expectations will lead to the widespread loss of trust in the potential of generative AI. 

In both scenarios, the brand, the authenticity of the company and its people and the approach to consumer relationships will become even more important. 

The second scenario will also amplify the consumer desire for authentic non-digital experiences. 

My advice to search marketers is to stay aware of the risks of AI and learn how different models work. What are their benefits and limitations? What tasks do they handle well or poorly?

Experiment with tools to boost your productivity. Many models aren’t yet ready for full marketing use, and treating them as such can worsen the issues mentioned in this article.

Dig deeper: How AI will affect the future of search

Original source: https://searchengineland.com/ai-winter-is-coming-446295

AI winter is a term that describes funding cuts in research and development of artificial intelligence systems. 

This usually follows after a period of overhype and under-delivery in the expectations of AI systems capabilities. Does this sound like today’s AI? 

Over the past few months, we’ve observed several key generative AI systems failing to meet the promise of investors and Silicon Valley executives – from the recent launch of Open AI’s GPT-4o model to Google’s AI Overviews to Perspective’s plagiarism engine and a ton more.

While such periods are typically temporary, they can impact the industry’s growth. 

This article tackles:

• A brief history of AI winters and the reasons each one occurred.
• Characteristics and lessons learned from past AI winters.
• Are we headed for an AI winter now?
• The future of AI in search and your role in it.

Brief history of AI winters and the reasons each one occurred

The field of AI has a rich (albeit quite short) history, marked by periods of intense excitement followed by somewhat of a disappointment. These periods of decline are what we now call AI winters.

The first one occurred in the 1970s. Early AI projects like machine translation and speech recognition failed to meet the ambitious expectations set for them. Funding for AI research dried up, leading to a slowdown in progress. 

Several factors contributed to the first AI winter. 

In a nutshell, researchers over-promised the capabilities of what AI could achieve in the short term. 

Even now, we don’t fully understand human intelligence, making it hard to replicate in AI.

Another key factor was that the computing power available at the time was insufficient to handle the growing demands of the AI field, which inevitably halted progress in the area. 

Some progress was observed in the 1980s with the development of expert systems, which successfully solved specific problems in limited domains. This period of excitement lasted until the late 1980s and early 1990s when another AI winter arrived.

This time, the reasons were more closely related to the death of one computing technology – the LISP machine, which was replaced by more efficient alternatives. 

Simultaneously, expert systems failed to meet expectations when prompted with unexpected inputs, leading to errors and erosion of trust. 

One key effort in replacing the LISP machines was the Japanese Fifth Generation project.

This was a collaboration between the country’s computing industry and government that aimed to revolutionize AI operating systems and computing techniques, technologies and hardware. It ultimately failed to meet most of its goals.  

Despite research in AI continuing throughout the 1990s, many researchers avoided using the term “AI” to distance themselves from the field’s history of failed promises. 

This is quite similar to a trend observed at the moment, with many prominent researchers carefully signifying the specific area of research they are operating in and avoiding using the umbrella term. 

AI interest grew in the early 2000s due to machine learning and computing advances, but practical integration was slow.

Despite this period being referred to as the “AI spring,” the term “AI” itself remained tarnished by past failures and unmet expectations. 

Investors and researchers alike shied away from the term, associating it with overhyped and underperforming systems. 

As a result, AI was often rebranded under different names, such as machine learning, informatics or cognitive systems. This allowed researchers to distance themselves from the stigma associated with AI and secure funding for their work.

From 2000 to 2020, IBM’s Watson was a prime example of the failed integration of AI, following the company’s promise to revolutionize healthcare and diagnostics. 

Despite its success on the game show Jeopardy!, the AI super project faced significant challenges when applied to real-world healthcare. 

The Oncology Expert Advisor, in collaboration with the MD Anderson Cancer Center, struggled to interpret doctors’ notes and apply research findings to individual patient cases. 

A similar project at Memorial Sloan Kettering Cancer Center encountered problems due to the use of synthetic data, which introduced bias and failed to account for real-world variations in patient cases and treatment options. 

When Watson was implemented in other parts of the world, its recommendations were often irrelevant or incompatible with local healthcare infrastructures and treatment regimens. 

Even in the U.S., it was criticized for providing obvious or impractical advice. 

Ultimately, Watson’s failure in healthcare highlights the challenges of applying AI to complex, real-world problems and the importance of considering context and data limitations.

Meanwhile, several AI-related trends emerged. These niche technologies gained buzz and funding but quickly faded after failing to live up to the hype.

Think of:

• Chatbots. 
• IoT (internet of things).
• Voice-command devices.
• Big data.
• Blockchain.
• Augmented reality.
• Autonomous vehicles. 

All of these areas of research and development still have a ton of potential, but investor interest has peaked at separate periods in the past. 

Overall, the history of AI is a cautionary tale of the dangers of hype and unrealistic expectations, despite also demonstrating the resilience and progress of the industry’s mission. Despite the setbacks, AI technologies have evolved. 

Dig deeper: No, AI won’t change your marketing job: A contrarian perspective

Characteristics and lessons learned from past AI winters

Generative AI is the most recent iteration in the cycle of AI breakthrough, hype, investment and multi-faceted technology integration in many areas of life and business. 

Let’s track whether it is currently headed toward an AI winter. But before that, allow me to briefly recap the lessons learned from each past AI winter. 

Each AI winter shares the following key milestones: 

Hype cycle

• AI winters often follow periods of intense hype and inflated expectations.
• The gap between these unrealistic expectations and the actual capabilities of AI technology leads to disappointment and disillusionment.

Technical barriers

• AI winters frequently coincide with technical limitations.
• Whether it’s a lack of computational power, algorithmic challenges or insufficient data, these barriers can significantly impede progress.

Financial drought

• As enthusiasm for AI wanes, funding for research and development dries up.
• This lack of investment can further stifle innovation and exacerbate the slowdown.

Backlash and skepticism

• AI winters often witness a surge in criticism and skepticism from both the scientific community and the public.
• This negative sentiment can further dampen the mood and make it difficult to secure funding or support.

Strategic retreat

• In response to these challenges, AI researchers often shift their focus to more manageable, less ambitious projects.
• This can involve rebranding their work or focusing on specific applications to avoid the negative connotations associated with AI.
• Then a niche breakthrough occurs, starting the cycle all over again.

AI winters aren’t just a temporary setback; they can really hurt progress.

Funding dries up, projects get abandoned and talented people leave the field. This means we miss out on potentially life-changing technologies.

Plus, AI winters can make people suspicious of AI, making it harder for even good AI to be accepted.

Since AI is becoming increasingly integrated into our countries’ economies, our lives and many businesses, a downturn hurts everyone.

It’s like hitting the brakes just as we start making progress toward achieving some of the world’s biggest tech-related goals like AGI (artificial general intelligence).

These cycles also discourage long-term research, leading to a focus on short-term gains.

Despite stalling progress, AI winters offer valuable learning experiences. They remind us to be realistic about AI’s capabilities, focus on foundational research and ensure diverse funding sources.

Collaboration across different sectors is key, as is transparent communication about AI’s potential and limitations – especially to investors and the public.

By embracing these lessons, we can create a sustainable and impactful future for AI that truly benefits society.

Let’s address the big question – are we currently headed toward an AI winter?

---

Are we headed for an AI winter now? 

It appears that progress in AI has slowed down a bit after an explosive 2023, both with regard to new technologies released, updates to existing models and hype around generative AI.

People like Gary Marcus believe that the big leaps forward in AI model performance are becoming less frequent.

The lack of breakthroughs in generative AI and new model developments from the leaders in the space suggests a potential slowdown in progress.

Judging by investor calls, mentions of AI have also decreased, leading more to believe that the productivity gains that generative AI promised would not manifest more than what has already been achieved.

Admittedly, it isn’t much. The ROI isn’t great. Many companies struggle to find the productivity returns expected from their AI investments.

The rapid advancements and excitement around tools like ChatGPT have inflated expectations about their capabilities and potential impact.

Something previously apparent to only a small fraction of the population, mostly AI researchers, is now becoming general knowledge – large language models (LLMs).

These models face major limitations, including hallucinations and a lack of true understanding, which reduces their practical impact.

People are realizing that these technologies, when misused, are already harming the web. AI-generated content has spread across the web, from social media comments to posts, blogs, videos and podcasts.

Authentic human-generated content is becoming scarce. Future AI models will inevitably be trained on synthetic content, making it impossible to avoid and leading to worse performance over time.

We haven’t even addressed the ease of hacking generative AI, ethical issues in sourcing training data, challenges in protecting user data and many other problems that tech companies often overlook in AI discussions.

Still, some signs point against an impending AI winter in the short term.

AI technology continues to evolve rapidly, with open-source models rapidly catching up to closed models and innovative applications like AI agents emerging.

Furthermore, AI is being integrated into various industries and applications, often seamlessly (sometimes not – looking at you, AI Overviews), demonstrating at least some practical value.

It’s unclear whether these implementations will meet the tests of time.

Ongoing investment in companies like Perplexity shows investors’ confidence in AI’s potential for search, despite skeptics debunking some of the company’s claims and questioning its tactics around intellectual property.

Dig deeper: Google AI Overviews are an evolution, not a revolution

The future of AI in search and your role in it

AI is undoubtedly here to stay. My fellow automation enthusiasts and I are thrilled that everyone is now excited about this technology and exploring it themselves.

It’s important not to let the current excitement raise your expectations too high. The technology still has limits and a long way to go before reaching its full potential.

Beware of tech bros and CEOs promising uncanny ROI or sharing their doomsday predictions of the day (always so, so soon) where there will be AGI and you will be replaced by AI. 

While automation is revolutionizing the workforce, change is gradual. 

Progress is being made toward AGI, but reputable AI researchers believe this reality will not come in the immediate future. Numerous obstacles must still be overcome to achieve this. 

Understanding any emerging technologies (especially those so widely discussed as AI is at the moment) and how they work is crucial to creating strategies that stand the test of time. 

What we might see happening (in search, in particular) is one of two scenarios. 

Progress continues

Implementations stand the test of time, and models improve. 

For search marketers, this might mean more AI-generated content to outcompete but also improved search systems and AI-detection algorithms, easing this task by amplifying human-written, authentic voices. 

Investors win. Big tech wins. Everyone wins. 

That is if we solve the challenges related to ethics, security, IP and resource use. But I digress.

Progress stalls

Systems become worse. Think:

• No improvement in Google AI Overviews.
• Even more spam in web results.
• Misinformation.
• Entirely poisoned social media feeds, online forums and other digital spaces. 

In this scenario, big tech will start bleeding money rapidly. (Some evidence suggests this trend has already begun.) 

AI systems are, at the end of the day, expensive to develop, maintain and improve. 

Failing to do so, however, will tarnish investor trust and they will eventually bow down to scaling back implementations in the area. 

The public failure of several of these technologies to meet expectations will lead to the widespread loss of trust in the potential of generative AI. 

In both scenarios, the brand, the authenticity of the company and its people and the approach to consumer relationships will become even more important. 

The second scenario will also amplify the consumer desire for authentic non-digital experiences. 

My advice to search marketers is to stay aware of the risks of AI and learn how different models work. What are their benefits and limitations? What tasks do they handle well or poorly?

Experiment with tools to boost your productivity. Many models aren’t yet ready for full marketing use, and treating them as such can worsen the issues mentioned in this article.

Dig deeper: How AI will affect the future of search

Original source: https://searchengineland.com/ai-winter-is-coming-446295

Home Business Magazine Online

The online gaming sector has created several new job roles, particularly in the areas of game development and graphic design. The increasing demand for game developers is evident, with the average salary rising from $88,010 in 2023 to $91,009 in 2024 in the U.S. The country holds 40% of the global workforce in this sector. The video game industry in the U.S. is projected to reach $90.79 billion by 2029. The salaries for graphic designers in the online gambling industry stand at approximately $49,800 annually, while UI/UX designers earn around $86,600 per year. These roles typically require proficiency in graphic design, computer science, or similar disciplines.

Online Table Game Dealers and VR Technologists

Online table game dealers have become integral to the experience offered by online casinos, aiming to replicate the traditional casino atmosphere. Deloitte’s study reveals that Ontario’s online casinos created nearly 15,000 jobs within two years. Growth projections for the online gambling market in Canada indicate it will expand by 6.39% from 2024 to 2029, reaching $5.71 billion by 2029.

Moreover, the U.S. casino gaming market is expected to grow at an annual growth rate/CAGR of 4.53% through 2027, with an annual addition of about 22,200 jobs in gambling services projected up to 2031 by the Bureau of Labor Statistics.

As technology evolves, Virtual Reality Game Developers and VR Experience Designers have emerged. The VR gambling market is estimated to grow by $1.74 billion from 2020 to 2025, with a 53.13% CAGR. This rising demand is attributed to the immersive nature of VR, offering players realistic gaming interactions.

Customer Relationship Management and Digital Marketing

Customer Relationship Management roles are increasingly prominent within the online gambling industry. The CRM software market for global casinos was valued at USD 1.12 billion in 2020 and expected to reach USD 1.68 billion by 2026, with a CAGR of 6.7%. CRM Managers and Social Media Integration Specialists at platforms such as Caesars online casino focus on player engagement and community building.

Simultaneously, the role of Growth Marketing Managers has gained traction. The global online gambling market, valued at USD 63.53 billion in 2022, is projected to grow at a CAGR of 11.7%, reaching USD 153.57 billion by 2030. Enhanced mobile usage and internet penetration necessitate robust digital marketing techniques to attract and retain users.

Emerging Roles: Esports and Responsible Gaming

Esports Betting Managers are now critical to integrating esports with online gaming platforms. The esports betting market valuation was USD 9.75 billion in 2021, expected to reach USD 35.56 billion by 2031 at a CAGR of 13.7%. This role focuses on managing esports betting offerings to appeal to esports enthusiasts.

Responsible Gaming Associates are becoming increasingly necessary as regulatory emphasis on responsible gambling grows. These associates support at-risk players and ensure compliance with regulations, aligning with the U.S. online gambling market’s projected growth at a CAGR of 16.52%, reaching USD 10.98 billion by 2029.

Technical and Analytical Roles

Fraud Analysts are essential for monitoring and preventing fraudulent activities within online gambling platforms. Advancements in AI and machine learning enhance these efforts, vital for the continued growth forecasted in the global online gaming market.

Data Analysts and Business Intelligence Analysts play important roles in deciphering large datasets to inform business decisions and improve efficiency. These positions reflect the increasing reliance on data-driven strategies within the industry.

Technical Support Engineers provide continuous support to ensure seamless gaming experiences, addressing any technical issues that may arise. The necessity for such support is amplified by the rising adoption rates of online gambling platforms.

AI and Machine Learning Specialists are pivotal in enhancing online casinos’ offerings. They develop AI algorithms to personalize gaming experiences, optimize marketing campaigns, and improve fraud detection, supporting the market’s competitiveness and growth.

The post Explosion in New Job Roles Related to Online Gaming appeared first on Home Business Magazine.

Original source: https://homebusinessmag.com/business-start-up/business-start-up-blog/explosion-new-job-roles-related-online-gaming/