How AI Changed My Workflow: A CEO’s Perspective
A personal journey of AI from a CEO embracing change
It’s nearly two years since ChatGPT launched to the public. GenAI is now a feature of our world whether we like it of not. But the exact path to riches has been distinctly gray. We are still some way off to fully understand the risks and opportunities, let alone take the right course of action.
One thing has come clear to me. I’m relying less on mainstream media, social media and opportunistic commentators, and more on individual perspectives. Only then do I get a realistic, personal and useful perspectives of their evolving use and relationship with AI.
I want to capture some of these one to one perspectives by recording podcasts. I’ve released eight episodes so far, which you can find on your choice of platform here.
There is one conversation so far that’s really struck a chord because of how much the technology has impacted him from a personal (CEO) perspective. I felt his story has the power to motivate and make us more curious to experiment.
Here are the highlights form the conversation with Johann van Tonder, CEO of AWA Digital - E-commerce CRO specialists. I hope you enjoy it as much as I did.
Q. Should we embrace failure to find our path with AI?
I’ve been obsessed with understanding the reasons behind the failure rate of AI projects, even before the ChatGPT days. As we record this, it’s almost two years since ChatGPT was launched, which really put AI on the global stage. Over the past two years, I’ve invested thousands of hours into exploring AI. If I look back, there’s a trail of failures—most of what I tried didn’t work out. Yet, the few successes I’ve had were so significant that they outweighed the failures. This experience taught me that progress doesn’t happen without setbacks.
It’s important to say that while the idea of ‘fail fast, fail often’ might sound cliché, it’s not about setting out to fail. I would spend entire weekends or late nights convinced that I was going to crack a solution, only to find that it didn’t work. But through those efforts, I learned what doesn’t work, and that’s often just as valuable as learning what does.
“Progress doesn’t happen without setbacks.”
Q. How has AI changed your daily workflow and personal approach to problem-solving?
AI has fundamentally changed my working life and behaviour. One of the most significant shifts has been the way I incorporate AI into my routine. For example, I take walks with my phone and AirPods, talking to ChatGPT as though I’m brainstorming with a colleague. These walks have become a source of inspiration and clarity—I come back with a full transcript of the conversation, ready to pull out actionable insights without pausing to jot notes constantly.
This practice has allowed me to harness spontaneous thoughts and get feedback in real-time. I now spend much less time searching on Google or responding to emails because I’ve reallocated that energy to interactions that bring me value. The AI acts like an ever-present aide that prompts me to think deeper and capture fleeting ideas before they’re lost.
“AI has become an ever-present aide, prompting me to think deeper and capture ideas in real-time.”
Q. What advice do you give to organisations looking to integrate AI?
I often get asked, ‘How do we use AI?’ and I always respond that this is the wrong starting point. The real question should be, ‘What problem are you trying to solve?’ Once you identify the problem, you can determine whether AI is the right tool and, if so, how to integrate it into your processes. AI shouldn’t be forced as an obligation—it needs to add value.
Curiosity is crucial. You might have a list of a hundred problems and you’re testing whether AI can solve them. You have to remain close to the problem and be willing to explore what works and what doesn’t.
“Start with the problem, not the tool.”
Q. What’s the role of leadership in AI adoption?
Early on, I tried to mandate AI adoption from the top down, but it led to resistance. Most people outside the AI bubble view it with scepticism, seeing it as hype or even a threat. I’ve since changed my approach—now, I share my passion for AI and openly discuss what I’ve learned. This transparency encourages those who are curious to explore it on their own terms, without pressure.
Leadership’s role should be to enable access to AI tools and create an environment where experimentation is encouraged. Don’t incentivise people to use AI as if it’s an obligation; it’s like incentivising someone to use the internet. It has to be an organic process where people find value themselves.
“Enable access, put guardrails in place, and let curiosity lead.”
Q. How do you encourage innovation within your team?
I’ve learned not to force AI on my team. Instead, I remain vocal about its potential and demonstrate its use in my own work. This sparks interest in some team members who then start experimenting on their own. There are those who embrace it and those who don’t, and that’s okay. It’s essential not to push too hard, especially in the context of current global trends of job insecurity and layoffs. People naturally associate leadership’s push for AI with job replacement, which fuels anxiety.
Transparency is key. When leadership promotes AI, there has to be clarity around the agenda—showing that it’s meant to enhance work, not threaten jobs. Trust is built through clear, honest communication.
“Transparency and trust are crucial when introducing new technologies.”
Q. How important is data and infrastructure for successful AI implementation?
Data maturity is a foundational element. Many organisations don’t realise their data weaknesses until they start using AI. As a personal example, I’ve created a ‘second brain’ by digitising everything—meeting notes, book highlights, podcast transcripts etc This allows AI to sift through and find connections I might have missed.
Businesses should begin by organising their data, even if it’s just a simple shared drive. The goal is to make information accessible enough so that AI can be applied effectively. When data is structured and available, AI can identify patterns and insights you might not even know to look for.
“Organise your data to unlock AI’s full potential.”
Q. How do you measure the success of AI adoption?
Measuring success can be difficult. We often focus on metrics that are easy to track, but they don’t always capture what truly matters. For me, the biggest returns from AI have been intangible—renewed excitement, enhanced creativity, and outputs of higher quality. While some might look for speed and efficiency, I find that AI sometimes takes longer but produces superior results.
Putting KPIs on AI use can distort its adoption. If you’re too focused on metrics, you risk stifling exploration and innovation. Sometimes, the best way to measure AI’s impact is to observe the improvement in quality and the renewed energy in the work.
“The real value from AI is often intangible—creativity, quality, and renewed enthusiasm.”
More valuable personal experiences will be shared at AI Pathfinder’s next quarterly AI Strategy Private Equity Breakfast Briefing on 3 December 2024 in London. Seats are limited, please register here.
