From banking to back offices, AI-powered agents are moving beyond copilots and becoming coworkers. Leaders must learn to manage machines like teams-or risk falling behind.
CIOs and business leaders are chasing AI value while drowning in marketing fluff, trending YouTube demos, and fearmongering headlines on every channel.
We’ve been here before. Electricity, steam power, the internet, the cloud—every era of meaningful tech change comes wrapped in fear, confusion, and the eventual realization that value accrues to those who figure it out fast.
We’re in that moment again. AI-enhanced agents aren’t just a feature. They’re the new architecture of enterprise productivity and value.
What’s an Agent, and Why Should I Care?
Tech boffins and marketers throw around the word “agent” with even more abandon than “digital” a few years ago. It’s all good fun until your trading floor reboots or your claims platform flatlines.
Ask 10 tech gurus what an AI agent is, and you’ll get at least 15 answers. But for business leaders, you only need one: an agent is a piece of AI-powered software that gets work done.
AI agents are the bots that help teams do work – writing code, testing applications, processing claims, redesigning legacy apps, identifying new drug combinations, triaging customer issues, rebalancing supply chains, and more.
Simply, an agent is code – AI-enabled software aligned to a goal. It senses the environment, reasons, decides, adapts, and acts. It may use other tools, collaborate with humans, or delegate work to other agents. You’ll often find them working together in a constellation of agents aligned to specific tasks in a business workflow.
In short: agents are the mechanism for AI to actually do work with business impact rather than being complex math and massive data sets. They are already reshaping how we work.
AI Agents Are Already Changing the Game
At Amazon, CEO Andy Jassy shared that GenAI tools have already saved 4,500 developer-years and generated $260 million in annualized efficiency gains. At Google, Sundar Pichai reports that over 25% of all new code is now generated by AI. And Dario Amodei, CEO of Anthropic, recently told the Council on Foreign Relations that within a year, AI could be writing nearly all code produced globally.
This isn’t about ChatGPT. It’s about a new architecture for work. AI isn’t just helping; it’s enhancing large portions of white-collar, knowledge-based work, starting with IT services, but now moving into other sectors.
- Salesforce paused technical hiring and laid off 1,000 people.
- Google launched a voluntary exit program for 20,000 workers, citing AI.
- DBS Bank (Singapore’s largest) announced plans to cut 4,000 roles, as agents now handle work previously done by humans.
- IT unemployment in the U.S. jumped from 3.9% to 5.7% in just one month (WSJ, Jan 2025).
The AI revolution isn’t coming. It’s here. And leaders need to understand how to start putting agents to work.
Your Digital Co-Workers Have Different Roles
Agents are not some sort of mystical beings, and not all agents are built the same — how they work with you depends on what kind of ‘digital teammate’ they are.
Think of agents like brilliant silicon-based interns – tireless, fast, and a bit naïve – that need help with executive functions. Some need supervision nearly every step of the way. Others can run more complex workflows with minimal oversight.
The range of capability, autonomy, and responsibility is vast—and understanding a simple taxonomy can be helpful.
- Task Agent: Handles specific, bounded tasks. E.g., generate test scripts.
- Workflow Agent: Runs a full sequence of steps across tasks. E.g., ingest data, clean, validate, and publish.
- Interface Agent: Engages with humans or systems to receive/give instructions. E.g., customer-facing assistant.
- Governor Agent: Oversees, validates, coordinates other agents. E.g., ensures quality, trust, compliance.
You wouldn’t hire a junior analyst to run strategy. Same with agents — autonomy and purpose matter.
| Autonomy ↓ / Purpose → | Task | Workflow | Interface | Governor |
| LOW Autonomy Requires human approval |
Copilot Agent Suggests or drafts, waits for input e.g., GitHub Copilot, Replit |
Guided Flow Assistant Orchestrates steps with checkpoints e.g., Notion AI, Salesforce Einstein, AAVA |
Conversational Assistant Gathers input, routes requests e.g., ChatGPT, Gemini |
Human-Supported QA Agent Flags issues, asks for review e.g., DeepCode, LangSmith, |
| HIGH Autonomy Acts independently |
Autonomous Specialist Executes narrow task start-to-finish e.g., FinOps bots, log analyzers, tagging tools |
Self-Running Workflow Agent Runs full processes without oversight e.g., Devin, CrewAI sub-agents |
Human Interface Agent Owns interaction and takes action e.g., OpenAI Operator, Inflection Pi, Rabbit R1 |
Meta-Agent / AI Manager Delegates and oversees agent teams e.g., CrewAI manager, LangGraph, Cognosys |
Real-World Example: AI Arbitrage in Action
Let’s move from theory to execution. What does this actually look like in a messy, real-world enterprise?
A major bank ran into a wall. They were operating a 40-year-old legacy platform with 900,000 lines of code (much of it in PL/1 from the 1960s), handling 900 million transactions per year, with over 100 approval workflows.
Using an AI platform purpose-built to close the last mile from insight to execution, our company (Ascendion) reverse-engineered 700,000 lines of code in just 3 weeks, analyzed 4,200+ use cases, and created a 3-year roadmap. This led to real business impact.
- Delivery at 1/3 the cost, 1/2 the time
- ~50% higher developer efficiency
- ~60% reduction in technical debt
- Modernized UX, alerts, and self-healing systems
- Secure, scalable architecture with zero business disruption
This is AI arbitrage – freeing up capital by shifting work from people to machines – in action.
Your Survival Guide: Five Moves to Start Managing Agents Now
It’s the early days of the true Digital Revolution – powered by AI. There are still a lot of questions, but a no-regrets path ahead for business and technology leaders is now clearing.
- Start with IT, but don’t stop there. Software development is the beachhead, but sales, marketing, customer support, and operations are next. If your business runs on knowledge work, you’re in scope.
- Carbon + silicon = the future of work. Humans (carbon-based) and agents (silicon-based) will work together. Successful leaders will reframe jobs to boost productivity with both — not just cut costs.
- Set new metrics for humans + agents building software. AI-enhanced delivery should shift target metrics: e.g., 80%+ agent-written code, 90%+ compliance, <50% time-to-delivery. Build new KPIs — for partners and your own teams — now.
- Redesign your technology teams. The best-performing teams in agentic delivery will have <25% traditional engineers and >75% working on validation, training, prompt design, and agent lifecycle management.
- Build your ecosystem. No one does this alone. Tools, platforms, model providers, integration teams, governance structures—you need a network. Build it.
Final Word: Wrangle the Agents, Win the Future
The signals are loud and clear. Wringing value from agent-powered work isn’t optional. It’s the new competitive capability. That means building systems, teams, and mindsets around augmented work.
It may be tempting to wait for the souffle to rise, for the technologies to harden and mature, for people to grow much more accustomed to working in new ways with silicon-based team-mates.
You could, but let history motivate you. We’re already passing the innovator phase and diving into the early adopter phase. Fast followers often outperform the pioneers (think: Microsoft after Netscape, Netflix after Blockbuster, Apple after Palm). But late-movers? They often fade.
In nearly every sector, the AI inflection point is here. You can pilot from the front — or get automated from the back. Leaders who embrace agentic AI now will unlock productivity, accelerate transformation, and leap ahead.
About the Author
Paul Roehrig is Chief Strategy and Marketing Officer for Ascendion and co-author of multiple award-winning, best-selling books. A recognized expert on business and technology, he has advised Fortune 500 leaders around the world; is a sought-after presenter at public, academic, and industry events; and is regularly featured in major publications. He lives in the Washington, DC, area with his family.
