Something extraordinary is happening inside the world’s biggest enterprises and it’s not just another digital transformation.
Across industries, a new kind of intelligence is emerging: Agentic AI where systems that don’t just assist people, but act on behalf of them.
From Automation to Autonomy
When PepsiCo’s Chief Transformation Officer Athina Kanioura declared, “We will be the first company to be agentic AI-first by the end of 2026, connecting all operations, strategy, and innovation,” she wasn’t just announcing another tech upgrade.
She was describing a new corporate metabolism.
Agentic AI isn’t about improving workflows; it’s about rewriting them.
Where automation once followed static scripts, agentic systems observe, reason, and adapt – turning ERP, CRM, and HR platforms from rigid databases into dynamic ecosystems that think and act in real time.
At the 2025 Dreamforce Conference, Dell Technologies’ CEO Michael Dell warned bluntly:
“If we don’t really get on this, a new company is going to come along and it’s going to put us out of business.”
Meanwhile, Accenture’s Julie Sweet reframed the moment not as a technical race but a leadership test:
“The first thing you have to do is say, ‘I’ve got to reinvent everything.’ It’s not just a small thing-it’s about reinventing.”
This is what makes the agentic era different. It’s not just about algorithms; it’s about ambition.
Why Enterprises Are Moving Agentic
BCG’s recent analysis shows that properly designed agentic systems can accelerate business processes by 30–50%, while reducing low-value work by up to 40%.
These AI agents can handle surges in data traffic, detect anomalies, and even correct themselves – no overtime required.
In enterprise contexts, this means:
| Function | Impact of Agentic AI | Example |
| Finance | Detects anomalies and reallocates capital autonomously | Reduces risk events by up to 60% |
| Customer Operations | document validation, end-to-end claims handling, and escalation | Cuts response times by 40% |
| Sales & Marketing | Adaptive campaigns that learn from customer behavior | Boosts lead conversion by 25% |
| IT & Procurement | Auto-resolving service tickets and rerouting inventory | Workflow cycles 30% faster |
In short, these agents act as tireless employees with perfect recall and instant execution – an always-on workforce that scales infinitely.
The Consultancies Powering the Shift
While US corporations are racing to declare themselves “agentic AI-first,” it’s the UK’s consultancies that are quietly mastering the blueprint for implementation.
Elsewhen is one standout.
Known for engineering autonomous agentic systems, the London firm has been embedding AI agents that replace multi-step workflows entirely – from procurement to customer care.
Their frameworks connect language models securely to enterprise tools, while generative interfaces adapt to user behavior in real time.
As one senior client put it, “We stopped managing tasks – and started managing outcomes.”
Aiimi builds the other half of the foundation: data environments where agents can safely operate.
Their work with government bodies ensures that AI is not just powerful, but compliant, auditable, and explainable.
At the deep-tech end, Cambridge Consultants are embedding agentic logic into hardware – from smart manufacturing systems to medical devices that self-regulate.
The connective tissue between all of them is clear: intelligence that acts, not just analyzes.
Lessons from the Field: Controls, Governance, and Trust
But autonomy without accountability is chaos.
As BCG’s playbook warns, companies must embed governance “from day one” – giving each agent a clear owner, access limits, and ethical boundaries.
The most advanced implementations follow three layers of control:
- Design Phase: Define autonomy thresholds and assign ownership.
- Build Phase: Enforce guardrails, sandboxing, and audit trails.
- Operate Phase: Monitor, log, and maintain human-in-the-loop oversight.
In other words, you treat agents the way you would treat a new hire – with credentials, a job description, and performance monitoring.
That’s how PepsiCo plans to manage its agentic ecosystem across supply chains, marketing, and innovation – every agent accountable, every decision traceable.
Reinventing Consultancy for the Agentic Era
For enterprise consultancies, this shift changes everything.
The traditional model of “design once, deliver once” doesn’t hold up when AI systems evolve daily.
The new playbook demands continuous orchestration – consultancies that design, deploy, and train evolving agentic ecosystems, not static solutions.
The most forward-thinking consultancies – from Elsewhen to Faculty to ICS.AI – are repositioning themselves as AI operators, not just advisors.
They build systems that learn from live operations and adjust autonomously.
Or as Elsewhen put it in their Planet Agent report,
“AI shouldn’t just predict the future – it should participate in it.”
The Road Ahead: Agentic AI as Enterprise DNA
By 2026, “agentic-first” won’t be a headline – it’ll be the baseline.
PepsiCo’s announcement may be bold, but it’s not unique.
From manufacturing to finance, the next generation of enterprise systems will be AI-orchestrated, continuously optimizing without asking permission.
The real challenge isn’t adopting AI – it’s adopting accountable autonomy: machines that act, adapt, and explain.
As Dell said, companies can either “become the ones that disrupt or be the ones that get disrupted.”
In the age of agentic enterprise, there’s no middle ground.
