Just two and a half years ago, generative AI was still mostly an open-ended debate. We talked about its potential over coffee, ran isolated pilots and wondered whether it would live up to the buzz.
Fast-forward to today, and generative AI is not just part of the conversation; it is the conversation.
It’s replying to emails, writing test cases, parsing reports, suggesting product features and sometimes generating entire marketing campaigns. And yet, despite this meteoric rise, one thing hasn’t changed: the unease.
The question I hear most often?
“Is AI here to take our jobs?”
When technology knocks, people transform
When ATMs arrived, people worried about tellers. But banks grew, and tellers became advisors.
The roles of the tellers didn’t vanish; they evolved.
Cloud computing’s arrival was expected to end IT. But what did we get instead? DevOps. Cloud architects. Site reliability engineers.
History has taught us this: Technology doesn’t erase roles, it evolves them.
AI is no different.
It’s not gunning for your job. It’s going after the burnout. The drudgery. The death-by-spreadsheet parts of your day.
The real power of AI? People.
While everyone talks about AI’s capabilities, the true differentiator isn’t the tech. It’s the team.
Because AI doesn’t magically transform organisations. People do.
When you enable your workforce to use AI, you don’t just improve output, you unleash potential.
A recent Zoom survey showed that 89% of workers say AI frees them from repetitive tasks. GitHub Copilot helps developers code up to 55% faster.
Burnout drops. Satisfaction rises. Decision-making improves.
The power boost you need: Agentic AI
Frameworks like Auto-GPT, LangChain and Microsoft’s Semantic Kernel enable AI to act autonomously: chaining reasoning steps, calling APIs and integrating with enterprise tools to execute complex tasks.
But this isn’t about replacing employees; it’s about amplifying them.
Imagine a marketer asking an AI agent within their project tool to research trends, draft a campaign and schedule posts. Or a support rep relying on an AI assistant embedded in their ticketing system to analyse a query, retrieve relevant content and draft a response. This isn’t future-speak. It’s already happening. Recent surveys show over 51% of organisations have tools enabled with AI or AI agents in production today.
These agents connect to business systems via APIs and SDKs, integrating naturally into workflows. With built-in guardrails like human approvals and access controls, they operate safely, transparently and within defined boundaries.
The result?
AI agents become digital teammates handling repetitive, multi-step tasks so people can focus on higher-impact work. They don’t replace jobs; they remove the grind.
This is real, measurable impact. But it’s not guaranteed.
Despite substantial investment and high expectations, only about one in four AI initiatives have delivered the return on investment companies anticipated, says a recent IBM study. Not because the tools aren’t capable, but because the adoption isn’t deliberate. Training gaps, resistance to change and poor workflow integration are the usual blockers.
That’s where leadership comes in.
Adoption is a journey — and it needs structure
As Robin Sharma mentions in his book The 5 AM Club, "Any change initially is difficult, later messy before it becomes Glorious." Gen AI and its usage in our day-to-day work are similar.
You can't expect a workforce to go from zero to AI-first without support. Adoption isn’t a toggle switch. It’s a process, and it needs to be led intentionally.
Several frameworks exist to guide this transformation. One I’ve found particularly useful is the USAGE framework. It's not the only one out there but is pragmatic and accessible.
USAGE stands for:
- Understand—Start by helping people understand AI and, more importantly, what it isn’t. Address misconceptions. Make the technology approachable.
- Support—Provide resources, training and psychological safety. Teams need time to learn without fear of making mistakes.
- Apply—Encourage the use of AI in real work, not side projects or demos. Let employees explore how it helps with actual tasks.
- Grow—As confidence builds, expand use cases and deepen capability. Create communities of practice. Share success stories.
- Evaluate—Measure what’s working. Are teams more productive? Less burned out? Are decisions better? Use that feedback to iterate.
Another solid model, STEP, developed by Paul Leonardi, is also beneficial for enhancing employee AI adoption.
Consistency and leadership involvement are key in using USAGE, STEP or a custom approach.
These frameworks remind us that AI is not a tool you install; it’s a capability you cultivate.
What happens when AI becomes the product
AI inside your organisation is powerful. But AI inside your product? That’s where things get really exciting.
Think Netflix.
80% of what users watch comes from its AI recommendation engine. In retail, 44% of repeat purchases come from AI-driven suggestions.
Infosys helped Financial Times cut support load by 31% using AI chatbots. Freshworks’ Freddy AI handles nearly half of all queries.
Even in healthcare, AI like Nuance DAX is saving doctors five minutes per visit.
AI is becoming a value layer, an experience enhancer and a competitive moat.
But what about the fear?
I get it. AI feels fast. It feels big. Sometimes it feels like it’s thinking faster than we are.
But here's the truth: AI can’t replace why you do what you do. It can’t replicate judgment, empathy or vision. It doesn’t have your context, customer nuance or gut instinct.
It can turn your 12-hour day into an 8-hour one or even an hour. It can also give you headspace for ideas.
Breathing room for innovation.
So what do we do now?
We lean in.
We upskill.
We stop treating AI like a sci-fi villain and start treating it like a team member helping us with our work.
AI won’t replace you. But someone using AI better might.
So let’s not get left behind. Let’s lead with humour, humility and a whole lot of human-first thinking.
Because in this next chapter of work, AI isn’t the star. You are.
Vasu Kothamasu is the General Manager of India & Global Engineering Leader at Contentstack. Follow him on LinkedIn, and read his previous articles here.
