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A key benefit of using artificial intelligence (AI) in business is the ability to accelerate responsiveness to your stakeholder needs. AI will help any company accelerate its operating cycles.

In our 2023 book Boundless, we introduced the SUDA model (sense, understand, decide, act) as the operating model for business in the age of AI. Any company’s ability to sense, understand, decide, and act is enhanced by AI, and that translates to a competitive advantage. These companies will be able to make more informed decisions more quickly — and gain what the military calls decision dominance and overmatch. 

Also: Six levels of autonomous work: How AI augments, then replaces

Of critical importance here is that a company’s success will depend on reducing the time between each stage of the SUDA model in order to shrink the delta between sensing and acting as close to zero as possible. Agentic AI will be the most effective way to reduce the time from sensing to acting, because AI agents can act on your behalf at all times.

The six levels of autonomous work show that each level of the model represents an increase in AI’s capacity in one of four SUDA stages as well as a general acceleration across the entire model at different scales of decision-making and action-taking — from the minute-to-minute activities of individual employees to end-to-end business processes to strategic, enterprise-wide initiatives. 

AI will accelerate and amplify both stage and scale. Companies that are not able to reduce their own Sense to Act delta will be overmatched by those that can. So what is decision dominance and why does it matter for how businesses will operate in the age of AI-powered economies? 

“Decision dominance,” according to US Army Futures Command chief Gen. John “Mike” Murray, “is the ability for a commander to sense, understand, decide, act, and assess faster and more effectively than any adversary,” The US military highlights why decision dominance matters and the key components necessary — including speed, range, and convergence. 

• Speed refers to the physical speed of weapons and also to the cognitive speed of an AI offering a commander options, enabling a commander make faster and better-informed decision as result – leaving the enemy commander a fatal step behind.
• Range refers to physically outreaching the enemy and prepositioning the right forces, gear, and supplies. “The quickest way to get from Point A to Point B is to already be at point B,” said General Murray.
• Convergence refers to connecting different Army and even non-Army systems on a common data-sharing network, as at the Project Convergence wargames last fall, Murray said. But it also refers to bringing together different institutions, whether across the Army or between the Army and private industry.

To achieve a SUDA model operating at the machine level is not just about technology and advanced uses of AI.  “It is much more than technology,”  Murray said. “It’s about what we will fight with but it’s also just as much about how we will fight, and how we are organized for that fight. It’s about scaling.” 

Machine power multipliers applied to each stage of the SUDA operating model will create abilities beyond human capabilities. AI will not merely progress to being more productive compared to individual human full-time equivalents (FTEs) or being measured in manpower units (as we discussed in our previous article on AI, horses and humans). AI will come to be measured in machine power — not simply in terms of GPUs/CPUs or transactions per second (TPS) but probably as some function of complexity, accuracy, and speed. 

AI is advancing so rapidly that we are creating a new digital workforce to do our jobs for us. AI-powered capabilities are growing in orders of magnitude annually. By leveraging AI’s predictive and analytical capabilities, companies make informed decisions that benefit their bottom line, society, and the environment. 

Also: AI can help businesses design for positive externalities

As agentic AI adoption increases in business, and actions can be taken 24/7 on behalf of human workers, we will see the emergence of a new measure of productivity — “machine power” or something similar. This measure will be needed to represent how machines will no longer just do “human” jobs faster, more accurately, and cheaply. They’ll also be doing jobs that we can’t do, jobs far more complex, with more inputs to handle, more moving parts to orchestrate, and less time to solve.

Managing robotaxi fleets — the latest innovation in the centuries-old ride-for-hire service that no longer employs human drivers or horse “engines” — will be an early example of this new machine power. Managing fully autonomous companies will be another.

What does agentic AI and machine scale SUDA business operating models mean for the future of work? 

Also: Welcome to the AI revolution: From horsepower to manpower to machine-power

Decision dominance, achieved through machine-scale SUDA operating models and powered by agentic AI capabilities, will allow businesses to massively shrink the time between sensing, understanding, deciding and acting to nearly zero. To stay relevant in an AI-powered economy, the currencies that matter most are speed, scale, intelligence, personalization and — most importantly — trust.

 Businesses must plan and design for instability. AI will play a crucial role in assisting leaders and their teams in making strategic — as well as immediate — data-driven decisions and taking effective action.

This article was co-authored by Henry King, business innovation and transformation strategy leader and co-author of Boundless: A New Mindset for Unlimited Business Success.