Fred Laluyaux is Co-Founder and CEO of Aera Technology, a leader in agentic decision intelligence transforming enterprise decision-making.
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Imagine an enterprise that never sleeps, one that continuously senses what’s happening across your business, evaluates the options, decides on the best course and acts, while your people focus on the decisions only humans should make. That's not a thought experiment anymore; it's happening now.
Across industries, a new model is taking shape, redefining how decisions are made and executed at scale. It's powered by decision intelligence: the ability to turn continuous understanding of the business into coordinated actions, in real time, within defined business constraints. This is what brings true autonomy to AI and enables the enterprise to become self-driving.
In this model, the shift is simple but profound: from people making and executing decisions supported by machines, to machines making and executing decisions guided by people. The result is a powerful partnership between human judgment and machine efficiency, unlocking a new level of performance for the enterprise.
For decades, organizations invested in systems that brought structure, consistency and visibility to their operations—a foundation for global scale and operational control.
But now, something more is possible.
The pace of business has accelerated. Decisions now happen at the level of customers, products and transactions. Organizations operate across ecosystems spanning suppliers, partners and customers. The opportunity in front of us is to move beyond systems that record what has happened, toward systems that actively shape what happens next. The self-driving enterprise emerges from this shift: an organization that continuously senses, decides and acts.
The rapid advancement of AI, particularly LLMs and agentic systems, has accelerated this transformation.
The intelligence inside your business can now act on what it knows, not just report it. Information once siloed can now be understood in context, connected across domains and translated into coordinated action.
Consider the parallel with self-driving cars. We pioneered the concept of "the self-driving enterprise" at Aera Technology in 2017, when autonomous cars were still largely prototypes. Today, you can hail one in San Francisco, and the newest are designed for autonomy from the ground up, with no steering wheel, operating in a connected, intelligent and optimized network. Every vehicle learns from interactions across the fleet, and that knowledge is redistributed in near real time. The fleet improves together, compounding its intelligence. That’s what the enterprise is now experiencing.
Gartner predicts that "by 2027, 50% of business decisions will be augmented or automated by AI agents using decision intelligence." These agents operate with clear goals, understand context, coordinate actions and continuously improve based on outcomes. What's powerful is how these agents connect planning, execution and optimization into a seamless flow of decisions.
As this transformation unfolds, something important is shifting in how the best organizations think about their operations.
Data remains essential, but the center of gravity is moving toward decisions: how they’re made, executed and improved. Strategy connects directly to execution. Organizations respond more effectively to change. And teams spend more time shaping outcomes rather than assembling inputs.
Within this decision-centric model, knowledge becomes part of the operating fabric of the enterprise. It’s captured through every decision, shared across the organization and continuously refined. The result is an enterprise that becomes smarter every day.
The impact of the self-driving enterprise extends beyond technology into an organization's structure and experience.
One of our partners, for example, has transformed its global supply chain through real-time decision orchestration across planning, inventory and logistics. The system continuously detects aging stock, rebalances supply and demand, automates routine decisions and optimizes logistics flows. Within 90 days of going live, the company prevented 200,000 cases of waste, saving $5 million in the first six months, or $10 million annualized. Inventory fell, cash flow improved and emissions dropped.
And that’s just the beginning. The company's chief supply chain officer recently projected another $50 million in cost savings and $100 million in inventory reduction over the next two years—value created proactively rather than recovered after the fact. That’s what becomes possible.
As decisions flow seamlessly across functions, organizations become more adaptive. They respond faster, operate with greater alignment and collaborate more effectively. The barriers between teams dissolve, replaced by a shared understanding of goals and outcomes.
At the same time, people’s roles become more meaningful. With routine decisions handled by an intelligent system, individuals focus on where human insight matters most: defining direction, exploring opportunities and solving complex challenges. This creates a workplace that's more efficient and engaging.
Organizations are deploying decision intelligence today, making thousands, even millions, of decisions each week with speed and precision. Examples like this are becoming more common across manufacturing, finance, pharmaceuticals, retail and energy. What once required bold experimentation is now delivering impact at scale.
For self-driving cars, what was once a question of trust is now a matter of safety record: Autonomous vehicles have proven more reliable than human drivers. Decision intelligence is on the same trajectory. Governance is built into the system from the start—every recommendation transparent, every decision traceable, every outcome measured. Just as autonomous vehicle manufacturers do, enterprises now think in levels of decision autonomy, from basic support to fully autonomous systems that humans supervise and govern. Organizations are no longer asking whether to trust it. They're asking how much to scale it.
That’s the self-driving enterprise: continuously learning and dynamically adapting, with decision intelligence at the core of everything. It brings people and technology together, amplifying the strengths of both.
The question is no longer whether this is possible; it’s how fast you want to move. And the answer starts with a single automated decision.
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