Since the 1940s when the term Artificial Intelligence was first coined, the aspiration has always been to build a machine that can think and behave like humans. Over the last decade, we have made incredible progress in this direction and today the machines in many ways have achieved human intelligence traits ... a new Species has emerged which we call the "Homobots".
At this unique point in history where there is convergence of Human and Artificial Intelligences, it is important to understand that there will be friction and fear until a new equilibrium is established. The prudent path would be for us to leverage our experience with Human Intelligence to smartly manage Artificial Intelligence.
This is the sentiment I have heard from many Small to Medium Business owners. The anxiety and need for action are legitimate, and deservedly so. What if I tell you that the answer lies in a pivot you are already capable of making: from managing Human Intelligence to managing Artificial Intelligence to benefit humans?
Think about what it means to bring someone new into your organisation. You identify a gap. You define the role: what needs to get done, what good looks like, what you can afford. You onboard, set expectations, and manage performance. When something isn't working, you course-correct.
The logic of bringing in an AI application is no different. Same gap, same brief, same performance expectations, same accountability.
You have been managing Human Intelligence all your life. Now augment it with Artificial Intelligence, keeping in mind:
"AI cannot and will not solve all your problems. It will solve some, and it will introduce new ones you are not yet equipped for."
The market is loud. Vendors overpromise. Consultants manufacture urgency. Peers claim their competitors are already ahead, a fact rarely verified.
The antidote is one question asked before anything else:
What specific problem am I trying to solve, and what does a good outcome look like?Every vendor, every demo, every peer recommendation gets filtered through that brief. If it cannot answer that question clearly, it does not belong in the conversation.
AI is not an incremental upgrade. It is as transformative as the internet was in the 1990s, changing not just what gets done but how work flows inside your company and across your ecosystem. New tools, new processes, new skill requirements will emerge. The businesses that adapt are the ones that treat this as a resourcing challenge, not a technology challenge.
That means finding the right AI application for your specific context. The same judgement you apply when recruiting people applies here.
"When you have a bumpy road, a flashy Ferrari that gets everyone talking is not the one for you. Find the vehicle that is best for your road in terms of reliability, comfort and performance. Your AI need is radically different from that of a Google or NVIDIA. The goal is not the most impressive AI in your stack. It is the right AI application that delivers consistent value with minimal oversight."
Every AI tool is designed to impress. The demo is the interview, carefully staged, running on ideal data, performing exactly the tasks it was built to excel at.
This is not a reason to hesitate. It is a reason to evaluate carefully, set expectations clearly, and build in the review process that every new addition to your team deserves.
These are not new skills. They are the same ones you have applied to every good hire you have ever made.
You have spent years building the instincts to find the right person for the right role, manage their performance, and make the hard calls when something isn't working. Instincts honed by Homo-sapiens over millions of years will be your greatest advantage in the age of Homo-bots. The only shift required is where you point them. Stop waiting for the perfect moment or the perfect technology. Define the role, find the right application, manage it like you mean it, and start before you feel ready. The businesses that win this decade will not be the ones that understood AI the best. They will be the ones that managed it the best.
Start by defining a specific problem you want to solve and what a good outcome looks like. Then evaluate AI tools against that brief, exactly as you would evaluate a candidate against a job description. Pick a low-stakes pilot project to test before committing to anything significant.
Hire for fit, not prestige. The most powerful and expensive AI is almost never what a small or mid-sized business needs. Define the specific task, the expected output quality, and your budget, then find the tool that meets that brief with minimal oversight and maintenance.
AI cannot and will not solve all your problems. It will solve some, and it will introduce new ones - including over-reliance, accountability gaps, and confident-sounding outputs that turn out to be wrong. Managing these risks requires the same structured oversight you would apply to any new team member.
No. The skills that matter most for AI adoption are the same ones that make a good manager: defining clear roles, setting expectations, evaluating performance, and knowing when something is not working. Technical knowledge helps but is not a prerequisite.
Both require you to define the role before evaluating options, assess fit over prestige, run a trial period, build in performance reviews, and manage ongoing output. The discipline of a good hiring process - multiple evaluation rounds, varied perspectives, and probing for weaknesses - is the same discipline that separates good AI decisions from expensive mistakes.