However far along their AI journey they may be, most businesses are currently struggling with a similar question: where to draw the line between human and AI work, and how to manage the handoff.
Task delegation is an increasingly fine balancing act given AI’s widening set of capabilities — for example, agentic AI ‘swarms’, or specialized AI agents that autonomously work together as a team without human intervention, are being touted as the next big leap in AI-based automation.
But automating tasks and workflows at will, without a detail-oriented examination of the context and suitability of each use case, is a dangerous game.
A blanket approach to AI implementation, or what Gartner’s David Pidsley termed an “automasochist” approach, could begin to crowd out human potential, diminish opportunities for career progression and actually decrease the quality of business outcomes — with the expertise of humans overlooked.
So the process of delineation – of deciding what should and shouldn’t be AI-assisted or automated – is essential to ensuring that businesses don’t automate tasks best suited for humans, or apply AI where it isn’t necessary or appropriate.
The question is, where does the line go? How much AI is appropriate for your business? To find the right blend, a decision-centric approach is key. Here’s why and how.
Starting with decisions
Good decisions are the essence of a successful business but decision-making is getting more complex all the time. A recent survey by Gartner reported that 65% of decisions are more complex (involving more stakeholders or choices) than they were two years ago.
In this increasingly complex business environment, improving decisions and their outcomes must be the guiding light for how AI agents should and shouldn’t be used.
So how do you become truly decision-centric and ensure that AI implementation is improving outcomes, rather than unnecessarily occupying human work?
At XpertRule, we start with understanding the decisions that make up your business, before pinpointing where AI can add value. We use decision intelligence to interrogate your decisions on a number of levels, such as:
- Value: The revenue or business value decisions deliver and the data, expertise, and effort they require.
- Source: Decisions might be made by people based on skills and experience, by machines based on programming, or by data based on insights.
- Complexity: Decisions might be logic-based and follow standard, predefined rules. They may need to refer to updated legislation. Or they may be decisions that need to be automated quickly and at high volume but with enough time to be reversed or reverted to human validation.
This diagnostic process, which interrogates how and why decisions are made, is enabled by the decision-mining and predictive analytics capabilities of our decision intelligence platform, viabl.ai.
Piece by piece, viabl.ai can map out the decisions that fuel your business and be used to intelligently design a best-case blueprint for how each decision should be handled at both a granular and big-picture level.
In effect, this is a process of reverse-engineering, by which you start with the decisions and outcomes your business wants and/or needs and work backwards.
This way, there are no square pegs in round holes; you end up only with the AI-based solutions that are appropriate for your business. Nothing more, nothing less.
Aiming for augmentation
Every organisation is currently trying to work out the right blend of AI-based automation and human decision-making.
There is a word for this perfect blend: augmentation.
But in order to ensure a truly augmentarian approach, human-AI collaboration should be appropriate and context-dependent. As we wrote in our last piece on Agentic AI, your AI agents need to understand the outcomes and decision-making processes your business is built on. Only then can they offer the right guidance to human experts, while closing the “last mile” gap between your data and outcomes.
viabl.ai ensures this balance of human expertise and AI assistance. It gives you an intuitive platform to design, build, manage and optimize your AI-powered workflows which can be used to support and augment your human decision-makers – essentially orchestrating your many AI agents and automating the handoffs between human and AI tasks.
For example, in insurance claims processing, if a claim is still suspicious after an agentic AI-powered conversation with the claimant, viabl.ai passes the claim on to a fraud assessor. viabl.ai determines when it is best to defer to an expert assessor, crucially keeping a human in the loop.
According to Gartner, 75% of global 500 companies will be applying decision intelligence to their businesses by 2026. Will your business be one of them?
Get in touch to start your responsible AI-powered decision intelligence journey today.
