Businesses want AI to do more than answer questions, write emails, or create reports. They want AI agents that can complete tasks, manage work, and make decisions on their own. But there is a problem. As companies adopt AI, very few are ready to give it that much freedom.
A recent Tata Consultancy Services (TCS) study, titled *Enterprise AI Study: Intelligence that is Real*, highlights this gap. The study finds that 84% of executives see better productivity as AI’s biggest business benefit. However, only 9% say their companies have AI agents that can safely manage work across different business applications.
Enterprise AI agent readiness is becoming an important measure of how prepared businesses are to move from basic AI tools to more independent AI systems.
This raises an important question: if businesses see so much value in AI, why do they still fear it working alone?
Businesses Want AI To Do More
Companies have been using AI to make everyday work easier. Employees use it to write emails, prepare reports, study information, and complete repetitive tasks. But AI agents can do more than respond to instructions.
You can give an AI agent a task, and it can work through several steps to complete it. For example, a company could use an AI agent to read customer complaints. It could check order details. It could draft a reply. It could send the issue to the right team.
This is a bigger step than simply asking AI to write an email.
It also explains why enterprise AI agent readiness is becoming important. Companies are no longer asking only whether AI can complete a task. They want to know whether it can manage an entire process safely.
The interest is clearly there. The TCS study found that 84% of executives see better productivity as AI’s leading business benefit. But wanting AI to do more and trusting it to work independently are two different things.
The Gap Between Using AI And Trusting It
One key finding in the TCS study is that only 9% of executives say their companies have AI agents. These agents can safely manage work across enterprise applications.
In simple terms, few companies are ready to let AI agents handle connected tasks across their business systems.
Consider the difference between asking AI to write an email and allowing it to manage a customer order.
Writing an email is a simple task. Managing an order may require an AI agent to access customer details. It may check payment information, update records, and communicate with different teams.
You can correct a mistake in an email draft before you send it. But a mistake made while handling a customer order could create bigger problems.
This is why enterprise AI workflows need careful planning. A company’s enterprise AI agent readiness also depends on how well it can manage these risks while allowing AI agents to complete tasks.
Companies must decide what information an AI agent can access, what actions it can take, and what should happen if it makes a mistake.
Why Are Companies Still Holding Back?
The TCS infographic also highlights how few companies are comfortable giving AI complete decision-making freedom.
Only 10% of executives say their companies allow AI agents to make decisions without human approval. This means most businesses still want people to stay involved when they make important decisions.
There are a few reasons for this.
First, AI agents often need access to company information to complete tasks. But giving them access to private customer details or financial records can create security risks.
Second, companies need clear rules about what AI agents can and cannot do. Without proper AI governance, businesses may find it difficult to control their actions.
Third, AI can make mistakes. Companies need ways to check their work and correct problems before they affect customers or business operations.
These concerns show why enterprise AI agent readiness is not just about buying new technology. It is also about preparing people, systems, and company rules to use it safely.
AI Needs The Right Information To Do Its Job
Another finding from the TCS infographic points to a problem that is easy to overlook. Around 44% of executives say business information sits in different systems. This makes it harder for AI to see the full picture.
Think about a company handling a customer complaint. To solve the problem, an AI agent may need the customer’s order details. It may also need payment history, past messages, and delivery information. But what happens if different systems store all this information and those systems do not work well together?
The AI agent may not get all the details it needs. As a result, it could give the wrong answer or take the wrong action. This is why connected enterprise AI workflows matter. Companies need to organise their information so AI agents can find and use the right details.
They also need human oversight, which means people must be able to check the AI’s work, correct mistakes, and step in when needed.
Giving AI more responsibility also means making sure the systems around it are ready. Without organised information and connected systems, improving enterprise AI agent readiness becomes much more difficult.
Is Using AI Becoming Too Expensive?
There is another challenge businesses need to consider: cost.
According to the infographic, 39% of executives are still checking if AI benefits are worth the cost. AI systems need computing power to work. The more companies use them, the more they may need to spend on these resources.
For example, an AI agent may save employees time by handling customer requests. But if it is expensive to run or needs constant checking, the actual savings may be smaller than expected.
This is why you cannot measure AI agent adoption only by how many AI tools a company uses.
Businesses must check whether these tools actually save time, reduce costs, or help employees work better. This is another important part of enterprise AI agent readiness because companies must understand the actual value of AI before expanding its role.
The same applies to enterprise AI workflows. Automating a complete process may sound useful, but companies must also consider the cost and the chances of mistakes.
What Does Enterprise AI Agent Readiness Look Like?
The TCS findings suggest that businesses still have work to do before AI agents can operate with greater freedom. But being ready does not mean allowing AI to make every decision without human involvement.
Companies can start by giving AI agents simple tasks that are easy to check. Once they show that they can handle these tasks correctly, businesses can slowly give them more responsibility. They also need clear AI governance rules, safe access to company information, and ways to review important decisions.
Human oversight will remain important, especially when an AI decision could affect customers, money, or private information.
This is a more careful way to use AI. It allows companies to benefit from the technology without giving it more control than they are comfortable with.
Ultimately, enterprise AI agent readiness means knowing which tasks AI can do alone. It also means knowing which tasks need supervision. It also means knowing when a person must make the final call.
DMT Take: The real test is how much control businesses give AI
The way businesses use AI is changing. Companies are moving beyond tools that simply answer questions or create content. They want AI agents that can complete tasks, manage work, and support business decisions.
But the TCS study shows that there is still a gap between what companies want AI to do and what they are ready to let it do.
Only 9% report having AI agents that can safely manage work across enterprise applications. Just 10% allow AI agents to make decisions without human approval. These numbers raise an important question about the future of business.
The next stage of enterprise AI may not depend only on how smart AI becomes.
It depends on whether companies can build the right systems. They also need clear rules. They must have strong security. Only then can they trust it with more responsibility. Because teaching AI to do the work is one challenge. Being ready to let it do the work is another.
Sources:
1. TCS Enterprise AI Study: Intelligence that is Real
2. TCS Official Press Release: Productivity Is the Top Benefit of AI
4. TCS AI for Business Study: Key Findings
See Also: Indian Startup Funding Falls: Why Investors Back Startups
Daksh Juneja is a performance marketing expert, trainer, and content creator featured in HT Tech. He helps businesses drive up to 4X ROI through Google and Meta Ads.
