## AI Is Changing Work Much Faster Than Expected

Businesses are getting exciting news and challenging news about artificial intelligence at the same time. Cognizant, a large technology company, released a major report in mid-January 2026 showing that AI can now do $4.5 trillion worth of work tasks in the United States. This is much more than experts predicted just a few years ago. The report studied 18,000 different work tasks across 1,000 different jobs to understand how AI could help.

What makes this finding special is the speed of change. In 2024, experts thought AI would affect work slowly. But now in 2026, AI is improving nine times faster than people predicted – going from 2% annual improvement to 9% annual improvement. This means AI's ability to help with work is accelerating quickly.

## More Jobs Are Affected Than We Thought

According to Cognizant's research, AI could potentially affect 93% of all jobs today. That sounds scary, but the report explains something important: AI is not replacing people – it is changing how work gets done. The study found that some jobs are changing especially fast. For example, legal work jumped from 9% AI exposure to 63% exposure. Education went from 11% to 49%, and healthcare practitioners went from 10% to 39%. Even CEO positions went from 25% to 60% exposure.

However, not all work is being touched by AI equally. The report found that 40% of management, business, and financial tasks still cannot be automated by AI. This shows that human thinking and decision-making remain very important in business.

## The Hidden Problem: AI Saves Time But Not Value

Here's where things get tricky for businesses. A report from Workday, another major company, discovered something surprising in late 2025. The report surveyed over 3,000 employees around the world in Asia, Africa, Europe, the Middle East, and North America. They found that 85% of workers are saving between one and seven hours per week using AI tools. That sounds wonderful!

But there is a problem hiding in these numbers. Only 14% of employees said they consistently get real positive outcomes from using AI. This means that AI is making work faster, but the quality is sometimes not good. The Workday study says that "nearly 40% of value is lost to rework and misalignment". In other words, employees spend time fixing AI mistakes instead of doing new work. This is called the "productivity paradox" – work is faster, but real value is not increasing.

The report explains what happens: instead of workers focusing on important, creative work, they are spending their extra time "correcting low-quality AI output and aligning conflicting guidance". When AI does something wrong or gives confusing answers, humans must fix it.

## Companies Are Not Investing in People as Much as Technology

When businesses spend money on AI, where does the money go? According to the Workday study, companies are directing "a larger share of AI cost savings to technology (39%) than to the workforce (30%)". This is backwards, according to the research. The study shows that when companies invest in training workers, those workers can use AI much better.

While 66% of business leaders say that training workers is a top priority, only 37% of employees who need the most training are actually getting it. The report also found something surprising about job descriptions: less than half of job roles have been updated to show what AI can do. This means "employees are using 2025 tools inside 2015 job structures," according to the Workday report.

## What Anthropic's Research Shows About Complex Work

Anthropicis an AI research company that looked at two million real conversations people have with AI in January 2026. Their research found something interesting: AI is helping with complex, higher-skill tasks much more than routine work. The study found that simple tasks were completed about nine times faster with AI help, while college-level tasks were completed about twelve times faster. This means AI is helping smart, complicated work the most right now.

Anthropicnoticed that tasks that would take a human worker about three and a half hours can be completed by AI through their API with a 50% success rate. This shows that AI can handle medium-length complex work. The company also found that people are learning to break big problems into smaller steps so AI can help better.

Interestingly, Anthropic discovered that almost half of all job types now use AI for at least some of their work. When the company looked at all its reports from 2025 and early 2026, they found that AI exposure went from 36% of jobs in early 2025 to 49% of jobs when looking at all the data. However, this changes when you consider how well AI actually does the work.

## Companies Worldwide Are Exploring and Using AI

Across the world, businesses are moving forward with AI. Research from Benefits Canada shows that in the United States, United Kingdom, and Canada, employers are rapidly trying AI. Among employers surveyed, 34% are already using AI in some way, and 49% are exploring how to use it. That means 83% of companies are either using or thinking about using AI.

What are companies using AI for most? According to the survey, 83% of employers are using AI for "text- and data-heavy processes" like reading documents and analyzing numbers. Companies also see AI helping with hiring (59% think it helps screen job applications) and with HR communications (50% think it helps). Companies in the United States, India, Japan, United Kingdom, and South Korea are leading in AI usage.

One thing that concerns business leaders: 30% of employers think AI will allow them to reduce staff and cut costs. This worry is shared by people like Geoffrey Hinton, a famous AI researcher, who warned that AI could cause "massive unemployment". However, a New York Federal Reserve survey found that companies using AI were more likely to retrain workers than fire them.

## The Cultural Problem: Companies Want More Without Giving More

There is another problem emerging in 2026 that businesses need to address. According to Gartner, a research company, many organizations are experiencing "culture dissonance". This means company culture no longer matches reality. Some companies are using a "startup-style culture" with long hours, tough performance management, and minimal flexibility, but employees are not getting extra pay, flexibility, or benefits to match.

A survey from Monster found that 73% of workers want higher salaries as their main priority for 2026. Yet many companies are expecting more work without offering more money or flexibility. Gartner warns that this is causing "regrettable retention" – unhappy employees stay in their jobs but are not productive.

Gartner also warns about something called "workslop" – this means low-quality work produced quickly using AI. When companies focus too much on using AI without focusing on quality, the work suffers. Additionally, Gartner notes that overusing AI at work can hurt employee mental health, and managers need to "spot symptoms of disordered AI use".

## What Businesses Need to Do Next

Experts agree that the next step is clear: businesses must invest in their people, not just their technology. Cognizant's CEO says that "human skilling becomes the bridge through which today's AI spending translates into tomorrow's tangible results". This means training workers is how companies actually get value from AI.

Cognizant suggests three key actions: develop digital fluency and adaptability in workers, create flexible business systems that can use new AI, and prioritize continuous learning. The company emphasizes that "human knowledge and judgment remain essential to harnessing AI's full potential". Where AI cannot help – like surgeons performing surgery or lawyers arguing in court – human skills like critical thinking and creativity will remain essential.

The bottom line for businesses is this: AI is powerful and is changing work faster than expected. But the companies that will succeed are those that use AI to help their people do better work, not replace them. Money spent on training and developing workers will pay off much more than money spent only on AI technology.