In this exclusive op-ed, Aleisha McCall, founder and CEO of Ultimate Edge Communications, argues that businesses risk confusing AI-driven productivity with genuine performance, warning that automating too much of the work could come at the cost of critical thinking, human capability and long-term commercial results. The piece comes ahead of McCall’s appearance at humAIn in Sydney on Tuesday 14 October, where she will moderate The Human Dividend: What Should AI Give Back? alongside Datacom director of AI Lou Compagnone and neurologist Dr Patrick Aouad.
I think we’re in danger of confusing activity with productivity, and productivity with performance.
We’re celebrating how quickly AI can generate content, strategies, reports, presentations and emails. But we’re not asking the most important question, “are we actually getting better at what we do, or are we simply producing more work, faster?”
I recently received an email from a very senior CEO; a long, well-polished email that, right at the bottom, read, “Would you like me to turn this into a PDF?” I remember thinking, WOW. This is exactly what concerns me with AI. And no, it is not one day being publicly caught or called out for using AI. I’m a huge advocate for AI and use it every day.
My concern is the huge back-and-forth of lengthy emails creating an enormous amount of activity, but very little strategic traction, no critical thinking or meaningful decision-making. Everyone feels incredibly productive, getting that instant dopamine hit from sending yet another polished response, but is anyone pausing to measure what they are actually achieving?
AI is making it easier than ever to create the illusion of productivity. The danger is mistaking the volume of work produced for the value being created and chasing the illusion of (false) organisational performance at the cost of individual talent and proficiency.
Friction vs good friction
Having competed at four World Championships in synchronised ice skating, I know that high performance is built through deliberate practice, repetition, failure, feedback and good friction. You can’t outsource the training and expect to develop the muscle. The same applies to our thinking.
I first stepped onto the ice at four years old. I spent years falling on the cold, hard ice, getting back up, repeating the same movements hundreds of times, pushing through frustration and learning that the greatest breakthroughs often came from the things I found hardest.
When I was learning my first Axel jump I kept falling on the same side. Over and over again. My coach and I had to continually analyse what was going wrong, experiment with different techniques, make corrections and repeat the process until I finally landed it. That’s good friction; anything that challenges you to become better, stronger, faster.
On the flip side, bad friction is just pure annoyance and wasted energy. It’s the squeaky door hinge that resists opening, or the clunky, ten-page checkout process on a website that makes you want to give up on buying something altogether. In short, bad friction just gets in your way.
The magic was in me doing it, overcoming that friction!
You don’t become a world-class athlete by watching someone else perform the difficult routines. You rely on your training and preparation to be able to perform in the moment.
Marketing teams and businesses are no different and would benefit from looking at an elite high-performance framework.
The Illusion of organisational performance
Organisations measure AI performance with what could be the most misleading metric: hours saved. But time saved doesn’t automatically translate into better decisions, stronger teams, better quality or improved commercial results. When I read that AI saves a marketing team 10 hours a week, I can’t help but wonder what happens to those hours. Are they reinvested into better strategic thinking, deeper customer understanding, creativity and improving campaign performance? Or are we simply filling them with more tasks?
If we continually outsource our thinking, problem-solving and decision-making to AI, we risk weakening the very cognitive capabilities that make us, humans, valuable. AI could be raising the ceiling on what organisations can produce while quietly lowering the floor of what their people can do independently.
That’s particularly concerning for the next generation of talent. Junior marketers have always developed their expertise by researching customers, analysing campaign performance, building strategies, writing briefs, making mistakes and learning to connect their decisions to commercial outcomes. The not-so-great first draft is part of the training. One of the biggest defaults to question is automating all the junior tasks: Do it too quickly and we remove the learning necessary to mould and create effective future leaders.
We can’t treat this as a productivity question alone, because faster output doesn’t guarantee sound judgement, stronger decisions or better commercial results.
More importantly, we can’t treat it as a wellbeing question alone, because reducing cognitive load and making work easier doesn’t build capability either.
Athletes operate on a cycle of high-intensity training with rest and recovery periods scheduled for a reason.
Design-first and technology second for long-term performance.
Just like our industry learned to differentiate between the long and short term of brand performance, we need to rethink how we view the entire marketing stack’s performance: People, processes, technology, learning and commercial outcomes. This is achieved by proactively asking: “How can teams remove the bad friction while reserving the good friction to protect future performance built on individual capability?” And “How can the capacity AI creates be reinvested to build better people, stronger teams and improved commercial performance?”
I’ve seen teams get this right. A CMO in the healthcare sector started with their people rather than the technology. They worked with the teams to break down the entire customer journey, to identify the (bad) friction points that were preventing better commercial outcomes.
They identified specifically what AI should take off people’s hands, repetitive administrative tasks, routine questions versus where humans could be more effective; improving customer conversations, solving conversion challenges and delivering a better customer experience.
When they introduced an AI agent to handle the repetitive enquiries and admin it freed the sales team to devote more of their time to higher-value customer interactions that, dropped contact centre time qualifying clients by as much as 50 per cent while lifting conversions by a stunning 20 per cent, with the same team.
The, design first and technology second approach preserves the training humans need to develop better judgement and technical proficiency.
The golden framework for marketers to adopt AI transformation
High Performance by Design means deliberately using AI to make people, teams and businesses more capable, not superficially more productive. Those who commit to this ethos will continue to develop competent people who can do the Critical, Conceptual and Creative thinking required, at least until the singularity of AI Superintelligence is deployed. In the interim, such a capable team will be able to proactively recognise when AI is wrong, and make the tactical corrections and strategic realignments to avoid reputational damage and ensure continued commercial growth and success.
It’s imperative to recognise that a human providing approval is not the same as taking responsibility and being held accountable for the outcome.
This means leaders need to measure success across four dimensions:
- Efficiency: What time, cost and unnecessary effort have we removed?
- Human capability: Are people becoming better thinkers, problem-solvers and decision-makers?
- Commercial performance: Are we actually improving acquisition, conversion, retention, profitability and/or growth?
- AI cost: What are the technology acquisition and ongoing token costs versus the quality (and value) of the output?
As is the case with physical muscle atrophy, The human capability that becomes hardest to recover is our ability to think independently, exercise judgement, solve complex problems and learn new skills. When we stop “doing it” our mental muscles weaken, become increasingly fragile and eventually ‘break’.
The question I want every leader to ask themselves before the next AI rollout is “Are you simplistically and superficially designing AI to replace as much of the work your people do, or are you deliberately leveraging it to both augment your people’s effective productivity while making them more capable with the technology?”
Five years from now, when you look back at the team you’ve nurtured and developed, and the skills they have and what you’ve achieved commercially, what story and result do you want to be?
That you got really good at getting AI to do things for you, or that you used AI to become more capable than you ever imagined possible?
The decisions you make today will define which story you get to tell or will be told about you.
Decide wisely.
Want to hear more? Check out her session tomorrow.
