What Marketers Are Getting Wrong About Agentic AI

Daniel Hulme is a globally recognised expert in AI. He's the CEO of the AI company Satalia, that joined the world's largest media company in 2021, WPP, where Daniel is now the chief AI officer. Daniel has been recognised as one of the top 10 Chief AI Officers globally.

Having received a masters and doctorate in AI at UCL, Daniel is also UCL's Computer Science Entrepreneur in Residence and a lecturer at LSE's Marshall Institute, focused on using AI to solve business and social problems.

Daniel is a serial TEDx speaker and is a faculty member of SingularityU. He has advisory and executive positions across companies and governments, and actively promotes purposeful entrepreneurship and technology innovation across the globe.

The next phase of the AI revolution is coming. WPP’s chief AI officer Daniel Hulme explores how businesses can cut through the hype and strategically prepare for the transformative potential of agentic AI.

The term "agentic AI" has become a popular buzzword, with Google search volumes surging significantly since February. This growing interest highlights the eagerness of companies to leverage its perceived potential. 

However, amidst the excitement, there's a critical misunderstanding of what agentic AI truly is and how it can be harnessed effectively. This misunderstanding risks leading businesses down a path of misdirected investment and ultimately, missed opportunities.

Understanding agentic AI: beyond simple decision-making

AI research has been cyclic over the past 70 years, oscillating between single-agent systems and multi-agent reasoning. However, we are now transitioning towards a new phase where multiple AI agents can collaborate to generate new knowledge and better problem-solving capabilities. In a multi-agent system, different agents with specialised knowledge can work together. For example, if one agent knows that Socrates is a man, and another knows that all men are mortal, they can only deduce that Socrates is mortal through shared reasoning and communication.

One common misconception is equating agentic AI with systems that simply possess agency or the ability to make decisions. While decision-making is a component, true agentic AI goes far beyond that. It’s not just about AI making isolated choices; it's about creating agents with distinct perspectives and reasoning abilities that can collaborate to solve complex problems.

Another misunderstanding is viewing agentic AI as merely a collection of personas or audience simulations. While these can be useful, they don't capture the essence of agentic AI, which involves dynamic interaction and communication between agents to generate new insights and solutions. 

WPP's approach to agentic AI solutions

At WPP, we're actively developing agentic AI solutions that embody these principles. Our Brand BrainsTM, which underpin our intelligent marketing operating system WPP Open, provide a prime example. Instead of relying on a single AI trained on vast amounts of data, we create a consortium of AI experts. Each expert focuses on a specific domain (e.g., tone of voice, imagery, written copy). This collaboration, mimicking how real-world experts work together, allows for the creation of higher quality and more nuanced advertising content.

We’re also developing AI Brains to represent various audiences, or even objective entities like food compliance or sustainability claims. This allows us to test content against these "representatives" to ensure it's not harmful or breaking any laws. This ethical and responsible approach is crucial when dealing with such powerful AI systems.

Avoiding pitfalls in agentic AI implementation

So, how can businesses avoid the pitfalls of chasing the "agentic" label without substance? Here are some key points to consider: 

• Focus on collaboration: Look beyond individual AI agents and prioritise systems that facilitate communication and knowledge exchange between them. This is where the true potential of agentic AI lies.
• Invest in reasoning: Don't be swayed by systems that simply regurgitate data. Seek out AI that can reason, break down complex problems, and generate new insights. 
• Seek expertise: Building effective agentic AI requires deep expertise in areas like multi-agent systems and symbolic AI. Partnering with specialists or building internal capabilities is crucial. WPP, with its deep bench of talent across the network and within our AI research company, Satalia, is well-positioned to guide businesses in this endeavour.
• Embrace the long game: Agentic AI is still in its nascent stages. Don't expect overnight miracles. Invest in research, experimentation and building a strong foundation for the future.

By shifting the focus from buzzwords to the core principles of agentic AI, businesses can unlock its true potential. This means moving beyond the hype and investing in systems that foster collaboration, reasoning, and ultimately, a more intelligent and effective way of solving complex problems. WPP is committed to being at the forefront of this AI revolution, empowering businesses to harness the power of agentic AI responsibly and effectively.