Agentic AI has arrived, but Gen AI’s problems aren’t going away. Here’s how Decision Intelligence can mitigate the risks and limitations of both technologies today.
Agentic AI has taken the business landscape by storm with the promise of autonomous agents accelerating just about every process and decision in your enterprise.
In a flash, the Gen AI copilots have been usurped by a team of 24/7 AI agents. But the problems of Generative AI haven’t gone away—unsurprisingly, given that Gen AI is powering the agents in question.
Let’s look at what that means for the application of Agentic AI.
Our need for Responsible AI is greater than ever
As XpertRule CEO Akeel Attar recently wrote, Agentic AI doesn’t pass the Responsible AI test. At a time when the European Artificial Intelligence Act (AI Act) has just entered into force, the notion of autonomous Agentic AIs making decisions with minimal human intervention should ring alarm bells for businesses.
On top of ethical concerns, Agentic AIs simply aren’t capable of coordinating with other agents and tying their actions up to overarching business objectives. Implementing Agentic AI is not just a case of figuring out what one agent does; it’s about coordinating the work and the plans of many agents, accounting for their interdependencies and tying them up to your overarching business objectives.
To carry out such complexity, there are three critical capabilities that are essential for the operation of autonomous Agentic AI:
As it happens, these are precisely the limitations of Gen AI, which “cannot be trusted to be accurate and consistent” due to lack of common-sense reasoning, as well as its shortcomings in workflow orchestration and planning. Current Gen AI Agent technology is incapable of reliably deploying an orchestration agent (or multiple agents) to coordinate with other agents and autonomously act as the orchestrator, guiding the way to meaningful outcomes.
Nor does Gen AI excel at logical reasoning, problem solving and planning tasks. While LLMs can learn patterns very well, they cannot be trained to make inferences from logical rules.
How to overcome these limitations and harness the power of Agentic AI?
Agentic AI needs an intelligent decision-making framework
AI is not about the cookie-cutter automation of menial tasks anymore. Enterprises now need to build systems that embody exactly how they want to run their businesses.
In other words, your AI agents need to understand the outcomes and decision-making processes your business is built on, in order to close the “last mile” gap between your data and outcomes.
Agentic AI might be able to conceive of and complete a chain of tasks but does it know what’s best for your business? Is it baked in with your blueprint for decision-making and integrated into existing software systems and human workflows?
As we explained in our Decision Intelligence whitepaper, this is what viabl.ai is built for.
viabl.ai gives you an intuitive platform to design, build, manage and optimize your AI-powered workflows – essentially orchestrating your many AI agents, whether in back-office complex transactions, or in nuanced front-office interactions.
Using viabl.ai, your business can execute multi-decision processes involving any number of different agents, people, or decision-engineering techniques, while applying the Responsible AI guardrails built into Decision Intelligence.
As Gartner's David Pidsley put it: “Decision Intelligence is AI for decisions.”
Decision Intelligence can integrate Agentic AI into your business — with immediate results
Despite all the hype, Accenture estimates that only 10% of companies have successfully scaled impactful use cases with Gen AI.
Invariably, businesses have lacked the framework to reliably and safely connect it to human workflows and high-impact use cases. But when Gen AI is implemented within a Decision Intelligence framework, the results are game-changing: from 90% reductions in pharma drug dossier review times to transforming the insurance claims decision process.
If Agentic AI is to live up to its promise, it’ll similarly need a Decision Intelligence infrastructure to connect it to meaningful outcomes for your business.
Get in touch with us to discuss integrating Agentic AI into your enterprise today.