Engineering AI Into Your Business
Rebuild Processes or Fall Behind
AI Alone Is Not Enough
A company’s success will not rest on AI agents themselves but on how those agents are embedded into business processes.
AI agents have crossed a threshold where they can generate text, code, designs, and even decisions at a quality level that rivals human knowledge workers. But the raw capability of a model, no matter how advanced, does not automatically translate into business value. Having access to a model is like owning a powerful engine without a car to put it in - impressive in theory, immobile in practice. What’s missing is the applied layer that makes the model useful inside day-to-day operations.
The true problem is that many organizations treat AI agents as end products rather than as building blocks. They adopt them as isolated tools - chatbots, copilots, dashboards - without engineering them into workflows where real value is created. The result is a growing gap between what the technology can do and what businesses actually capture. Unless executives shift focus from “having AI” to “using AI to get work done,” most investments will stall at the proof-of-concept stage.
AI agents alone are not the prize - the problem is converting raw capability into repeatable, outcome-driven business processes.
The Risk of Falling Behind
The consequence of failing to embed AI into workflows is wasted investment and lost competitive ground.
Many companies are already pouring millions into AI pilots, licensing models, and hiring talent. Yet, without redesigning the way work actually gets done, these efforts produce flashy demos but little bottom-line improvement. Studies of past technology shifts show the same pattern: tools alone don’t create value; it’s the process redesign around them that drives measurable outcomes. The risk is clear - firms that focus only on “AI adoption” will spend heavily and see little return.
Meanwhile, competitors who integrate AI into core workflows will achieve step-change improvements. They will reduce lead times by automating knowledge work, unlock new revenue streams by rethinking customer journeys, and cut costs by reducing rework and redundancy. The advantage compounds quickly, much like early adopters of cloud computing who rebuilt their operating models and soon outpaced peers on speed, scale, and profitability. For executives, the cost of delay is not neutral - it actively widens the gap between leaders and laggards.
The impact is stark - integrate AI into workflows now, or risk falling irreversibly behind in the next major business shift.
Three Paths to Applied AI
Executives must decide whether to treat AI as a bolt-on tool or to engineer it into the operating system of their business.
The strategic choice is not whether to use AI - everyone will. The real decision is how to apply it in ways that reshape workflows, unlock scale, and create defensible advantages. There are three viable paths forward, each with different payoffs and risks.
- Vertical AI Agents: Build domain-specific agents that integrate directly with legacy systems and line-of-business workflows.
- Benefit: Delivers targeted impact quickly by solving well-defined problems in finance, supply chain, or customer service.
- Risk: Narrow solutions may not scale enterprise-wide, potentially creating fragmented ecosystems of agents.
- Process Reimagination: Redesign entire business processes around the capabilities of AI agents.
- Benefit: Captures the full potential of AI to reinvent operations, creating breakthroughs in efficiency and customer value.
- Risk: Requires major change management, executive sponsorship, and cultural alignment. Disruption can be significant.
- Consulting & Infrastructure Plays: Partner with or build dedicated services that help industries adopt AI at scale.
- Benefit: Opens massive business opportunities similar to the rise of cloud consulting and infrastructure providers.
- Risk: Demands heavy upfront investment and patient capital, with slower time-to-value than SaaS models.
The winning strategy is not about shipping AI agents, it’s about engineering applied agents that reshape how work gets done.
Lead the Shift or Get Left Behind
Every choice about AI agents carries downstream effects on execution, investment, and long-term competitiveness.
If you focus on vertical agents, you gain speed and targeted wins. These projects are easier to implement, integrate with existing systems, and prove value quickly. But they risk creating silos of automation that don’t add up to full transformation. If you reimagine processes, the upside is far greater - entire workflows become faster, leaner, and more customer-centric. Yet this demands executive sponsorship, cultural change, and a high tolerance for disruption along the way. If you choose the consulting and infrastructure route, the opportunity is to build enduring platforms and services that shape industries. But this play requires deep capital reserves and patience to capture returns over years, not quarters.
The sharper contrast is between acting now and doing nothing. Act now, and you position your company as a leader in the next business revolution, much like the early cloud adopters who redefined their industries. Wait on the sidelines, and you risk replaying the cloud story in reverse: watching others rewrite the rules of competition while your business slips behind.
The consequence of inaction is irrelevance; the consequence of action is leadership in the era of applied AI.
Next Move
You must decide now how your organization will engineer applied AI agents - choose a path, appoint an accountable owner, and launch a pilot that ties directly to a core business process within the next quarter.
Dimitar Bakardzhiev
Getting started
