Why you can't ignore AI agents
Humans at the centre of a digital workforce can rapidly scale, adapt, and transform your business operations.
Much of the hype around AI is about individuals supercharging their own tasks.
AI agents change this.
They are the glue that links individual tasks together to be your digital workforce.
People still control what AI agents do, ensuring they are headed in the right direction.
Shape the future by refining the past
Established organisations on the front foot with AI adoption, focus on speed and innovation instead of just growing bigger.
They use smart tools, like AI Agents, to connect different types of AI systems into smooth workflows, helping them work faster, solve problems better, and keep costs under control.
And with automated operations, growth is much easier to achieve.
In software development, customer service, and drug discovery, AI agents are reportedly boosting productivity and reducing time-to-market by over half of what they used to.
AI agents designed for tax can produce complex documents in just a day instead of multiple weeks, while in finance, AI is transforming data analysis and enhancing both the speed and accuracy of audits.
AI Agents can redefine work and your workforce
To make human-AI teams a core part of your business, you don’t just focus on technology. It’s about rethinking all parts of your operations to work faster and drive more innovation with AI.
People are key but should focus on what only they can do - guiding AI, innovating with it, and making quick decisions. This means redefining roles, clear responsibilities, and smarter hiring strategies.
Your colleagues may soon lead teams of AI agents, needing not just new skills but a mindset that embraces AI and innovation.
Don’t let the tech dominate the conversion. Foster a supportive culture, offer incentives and reassurance about your colleagues vital roles in the AI-driven future.
New tech with a big future
AI agents use the same underlying capabilities as chatbots, like ChatGPT, but can act on their own, work together on big goals, and run entire workflows. It’s new technology, but the big names are already in.
OpenAI launched their AI agent solutions to consumers, Microsoft helps businesses create autonomous agents with Azure’s AI Agent Service, and Amazon’s Bedrock Agents has been around for over a year but increasingly more sophisticated.
There are also specialist AI Agents providers like CrewAI, and UiPath is transitioning from automation to AI Agents.
What you can do with AI Agents
Workflow automation and productivity are top use cases for organisations.
For example, if you receive thousands of documents from clients in multiple formats that need to be processed. AI agents can not only provide the automation of old via RPA (robotic process automation), but importantly now, they provide the context of each document.
Colleagues can also benefit with their individual tasks, for example needing to access all information on a client when writing a document, no longer requires them to be in their CRM, just a query using Microsoft’s Copilot can retrieve the answers and add directly to the document.
Customer service and support is another popular area for transforming work using AI Agents.
Companies like Dun & Bradstreet “allow clients to ask a question related to a company and an AI agent will ensure the data is the most accurate information related to that company.”
This feature would be a challenge without AI agents, since they are able to find the right company data. amongst many with similar names and addresses.
Bank of America provide customers with a virtual financial planner, called Erica®.
Erica® is an AI agent serving 42 million users with over 2 billion interactions, helping customers to do multiple banking tasks quickly and accurately, from paying bills to understanding complex financial products.
HR and employee support is a third example of AI agents in the workplace, with an IBM survey showing 43% of organisations use AI agents in HR.
Answering colleague questions and completing simple tasks on their behalf is common now for many organisations. This does still require accurate information on the questions that are asked, to avoid the agents retrieving answers that are generic to all organisations, when using generative AI.
Recruitment is an area that HR teams are becoming increasingly reliant on Ai agents, with CV retrieval and screening now a common use case, albeit with mixed outcomes. For example if the agent is retrieving CV’s based on the job specification, is the specification accurate? You’d think yes, but recruiting managers don’t always get this important task right.
HR teams that are iteratively improving the underlying data (e.g. policies and procedures) that AI agents are using to make decisions, are the ones that will see the greatest success.
Keeping AI Agents in Check
Safety is a priority for AI agents, but trust alone isn’t enough, businesses need robust systems to monitor and control them.
Tools that track agent behaviour, set boundaries, and evaluate performance are becoming essential to prevent errors and ensure accountability.
It’s not just about catching mistakes, it’s also about managing the legal and operational risks of deploying autonomous systems that use data at scale.
Without proper governance and thoughtful change management, businesses may struggle to fully benefit from the potential of AI agents.
Taking the time to plan and adapt upfront can pave the way for smoother implementation and faster growth down the line.
Sources:
Dun & Bradstreet launches ChatD&B™, Its Advanced Gen AI Assistant, https://investor.dnb.com/news/news-details/2024/Dun--Bradstreet-Launches-ChatDB-Its-Advanced-Gen-AI-Assistant/default.aspx
Bank of America’s customers can “Spend, save and plan smarter with Erica, your virtual financial assistant”, https://promotions.bankofamerica.com/digitalbanking/mobilebanking/erica