Agentic AI Explained: The Future of Decision Making

AI is more than a trend! The UK government’s adopting it into civil service, while tech giants are featuring it in our communications. What they’re not talking about is agentic AI. We’re taking a deep dive to compare traditional and agentic AI, how it could affect future decision making, the ethical concerns, and funding options for agentic AI innovation.

Whether you spend time scrolling social media or you Google absolutely every question that comes to mind, you’re likely encountering some form of AI content. 

Be it DeepSeek, Gemini, Llama or OpenAI, there’s no denying that AI (artificial intelligence) has changed the way we interact online, but could it change the future of decision making to streamline operations in the workplace?

With agentic AI, this could be a real possibility – and the future is closer than you think!

What is Agentic AI?

Imagine arriving at work, and seeing that someone has already completed the tedious tasks that usually make your morning drag. With agentic AI, this becomes a reality.

Agentic AI is an artificial intelligence system capable of performing tasks with little human oversight. It uses LLMs (large language models), machine learning, and reinforcement learning to autonomously analyse data, set goals and perform tasks. 

This enables agentic AI to adapt and improve its performance over time, reducing the need for frequent human intervention.

What Can Agentic AI Do

Given its capacity to solve problems, agentic AI has a wide range of applications that assists workers with repetitive tasks, freeing up time.

Using its key characteristics of autonomy, proactive behaviour and contextual understanding, agentic AI is currently used to perform tasks such as: 

• Portfolio management
• Risk management
• Network security
• Trend analysis
• Demand prediction

The Difference Between Traditional and Agentic AI

Although both traditional and agentic AI are able to provide assistance in the workplace, one of them is a rulebreaker that defies the idea we have of AI.

Traditional AI relies on preprogrammed algorithms or human intervention to analyse data and perform specific tasks, whereas agentic AI relies on adaptive systems to assess data and make decisions that automate dynamic tasks. 

This means traditional AI will review data sets to complete a task. Agentic AI on the other hand, will draw on previous experience with data to optimise and complete a task. 

Example of Traditional AI

There are many forms of traditional AI (such as recommendation engines and expert systems), but we’re going to focus on something that you likely have in your pocket. 

Siri is a voice recognition software that, when called upon, relies on preprogrammed systems to carry out a task. For example, if you asked Siri to skip a song, it can do so because the software is already made to do that. 

Example of Agentic AI

In terms of agentic AI, we’re going to focus on one that has had plenty of media attention.

Tesla uses agentic AI in their full self-driving system, allowing the car to learn from its environment and adapt its behaviour on the road. This improves safety and efficiency with little programming or human intervention. 

How Agentic AI is the Future of Decision Making

Many people aim to work smarter, not harder. With agentic AI, they may have the perfect solution!

Agentic AI can perform daily tasks, but it’s also transforming the decision making process. Its reliance on data allows it to see past human inclinations, making agentic AI the perfect partner in the workplace. 

How Agentic AI Assists in Decision Making

When it comes to decision making and agentic AI, there’s more to it than removing human bias. Here are some other ways that agentic AI can assist in decision making:

Ethical Concerns Related to Agentic AI

As with all emerging technologies, there are a range of ethical concerns about the use of agentic AI in the workplace. Some ethical concerns related to agentic AI include: 

• Bias in training data
  Decisions made by agentic AI can be affected by biases in training data, potentially leading to discriminatory decisions
• Lack of transparency
  Agentic AI is made up of complex algorithms, making it hard to determine how the autonomous systems reached specific decisions
• Over reliance
  Too much dependence on agentic AI can produce delays or disruptions should the technology malfunction
• Job displacement
  Overuse of agentic AI could lead to job losses which could cause economic disruption and displacement 

To ethically adopt agentic AI into daily practice, it’s important to have contingencies in place that include: 

Funding Agentic AI Innovation

As we begin to adopt the use of agentic AI, there’s still a lot of progress to be made.

The UK has a range of funding opportunities for businesses investing in the research and development of agentic AI, adapting it to suit specific needs. Agentic AI funding opportunities include:

• Innovate UK
  Part of the UK Research and Innovation (UKRI), Innovate UK oversees a range of funding programmes for AI innovation
• Safeguard AI
  Part of the Advanced Research and Invention Agency (ARIA), the safeguard AI programme provides funding for projects with a direct focus on the safety and ethical concerns of AI systems
• R&D Tax Credit Relief
  Overseen by HMRC, the R&D tax credit relief offsets a portion of the cost of research and development for qualifying scientific and technological projects

R&D Tax Relief for Agentic AI

R&D tax credits are designed so businesses investing in scientific and technological advancement can reduce their corporation tax. This means that businesses investing in agentic AI research and development could qualify for the relief – although they must align with eligibility criteria. 

For a business to qualify for R&D tax credits they must be liable for UK corporation tax. 

Project eligibility is a little more complex, as HMRC requires projects to make an advance in knowledge or capability. They state the advancement must be made by overcoming a scientific or technological uncertainty. This is what HMRC has to say on uncertainties:

“A scientific or technological uncertainty exists when an expert on the subject cannot say if something is technologically possible, or how it can be done, even after referring to all the available evidence.“

HMRC, Check if you can claim R&D tax credits

Agentic AI projects that meet the eligibility criteria for R&D tax credits, can reclaim a portion of the following costs: 

• Direct staff costs (including PAYE, pension and NIC contributions)
• Externally provided worker costs
• Software costs (used directly in research and development)
• Test stage prototypes
• Collaborative working (for businesses working with research organisations and charities)

Secure R&D Tax Relief with Alexander Clifford

As one of the UK’s leading R&D tax credit advisories, our specialist team has a deep understanding of HMRC’s policies and processes. We’re here to ensure that every qualifying activity and expense is identified, helping you maximise your claim with accuracy and care.

With a track record of securing over £83 million in tax credits for our clients, we’ve proven time and again that your innovation deserves to be rewarded.

That’s what makes Alexander Clifford your trusted choice for R&D tax credits.

Don’t let the value of your groundbreaking work on agentic AI go unclaimed. Take the first step today by filling out the contact form below or booking an appointment with one of our specialists.