This essay as told is based on a conversation with Geetha Rajan, director of the global strategy team at Freshworks, a SaaS company. It is based in the San Francisco Bay Area. His identity and employment have been verified by Business Insider. The following has been edited for length and clarity.
I am a Director on the Global Strategy team at Freshworks, where I lead high-priority strategic initiatives that shape the company’s growth, investment decisions and execution, including around AI adoption.
Previously, I spent nearly a decade at PwC advising Fortune 500 companies in healthcare, financial services, and technology on growth strategy and digital transformation. In my role, I led the upskilling of more than 50,000 employees on automation tools.
Technology transformation has always happened, but cloud or mobile transformation took at least 10 years to be fully adopted. ChatGPT reached millions of users in the first few months.
Many employers will continue to expect that you use AI every day without really understanding the consequences. It’s the pressure that leads you to make more mistakes rather than using them thoughtfully.
These are some of the the mistakes I see employees make do when adopting AI:
1. Go from 0 to 100% overnight
Many people are trying to go straight to Iron Man and fully automate their workflow. It should be a process. The first step is to treat the AI or technology like a super intern, so that you have the most control over things while giving it little action.
For example, if you start by providing structured data, but verify each output. AI can hallucinate beautifully formatted output.
2. Outsourcing strategy and thinking
I am a consultant and strategy advisor. So in terms of ideation and thinking, that’s the one part that I generally don’t leave to AI.
This is due to extensive experience in the field of consulting and participation in the labor market itself. I want to first mentally write down my model and first principles. I definitely check the numbers and even try to extract unstructured data from AI, but I always write my first draft very rigorously, keeping my first principles hat on.
After you finish a draft, you can ask him to poke holes in it and say, “Hey, you’re the most skeptical board member, or the CFO, poke holes in my strategy.” »
Many of the AI outputs are really neat. But if you don’t have that insight, if you haven’t seen this enough times, you can’t tell whether an AI is actually making a mistake or not. This is where a lot of work fall is coming: You just take the AI output and throw it into an email or analysis.
I made this mistake myself, where I had five or 10 minutes, and I asked AI to quickly write down some design principles for me and present them on a slide. During my presentation, I was like, “Wait, I don’t think that makes sense, and that’s not actually what I was trying to say.” I actually embarrassed myself.
You can also easily find yourself in a situation where the language the AI uses is not something you would use colloquially or even in a professional setting.
Sometimes my biggest worry is what will happen five years from now – when no one has actually done the initial work and we burn the ladder trying to climb it. As much as AI can do things, I think it’s more about the commitment to yourself than continuing to learn problem-solving skills and using Excel.
3. Approach AI without context
You need to know exactly who you are solving for and what the purpose of solving this exercise is.
For example, if you are building an AI model to understand your business’s customer segments, you still need to know your segments at a high level. This is the part I would never outsource. If you don’t have that context yourself, you could go in a million directions.
The fundamental things about taste, process, architecture, how you build things don’t come from any tool, whether you’re using ChatGPT or the latest model. If the AI gives you 50 ideas, you need to know which of them will stick. As an employee, it is your responsibility to choose the right one, so you need the insight and expertise to do so.