Why the tech leaders treat AI as a multiplier, not a substitute.
Artificial Intelligence continues to take pride of place in a lot of workplace convos heading into the backend of 2025. For every headline about productivity breakthroughs, there’s a counter-argument about job losses.
But across our AI & Data leadership community, one theme consistently stands out: the biggest wins are seen when AI is used as a "force-multiplier", not just purely a replacement.
Leaders who reframe AI as augmentation rather than automation are building more capable, innovative, and resilient teams.
But what does that look like in practice? Here's some of our top tips and recommendations to keep in mind when deciding to onboard AI.
1. Adopt the "multiplier mindset"
AI works best when it frees people from low-value, repetitive work so they can focus on higher-value, complex, and creative tasks.
Case Study: Renault’s Geospatial Data Success
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The challenge: Geospatial analysis required 3–4 specialist scientists to run complex queries on traffic, competitor locations, and polygons.
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The solution: AI tools began writing queries, handling the complexity almost “out of the box.”
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The result: Within two months, business users could generate maps and analytics themselves, without specialist support.
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Why it worked: Users had the domain knowledge to validate AI outputs. The tight feedback loop between people and AI kept quality high while delivery accelerated.
This is augmentation in action: using AI to extend human capability, not erase it.
2. Why “replacement” thinking in AI can fail
Treating AI purely as a headcount reduction often backfires. The hidden costs of this can include:
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Missed innovation when you remove the people who understand business context better than AI.
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Cultural resistance from teams who feel threatened by the tools and often don't want to jump on board straight away.
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Slower adoption when employees aren’t part of the journey or understand fully the 'why' behind using it.
The most successful leaders we’ve seen frame AI as a collaborative tool, keeping teams engaged and invested in making it work.
3. Keep humans in the loop
Even advanced AI models need guidance. “Set and forget” can lead to mistakes
Keeping experts involved ensures:
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Errors, biases, and 'AI hallucinations' are caught early.
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Outputs are validated before influencing decisions.
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Models improve through real-world feedback.
Think of AI as an apprentice: capable and fast-learning, but still in need of a mentor.
4. Communicate the vision
How leaders talk about AI shapes how teams adopt it. To drive confidence & uptake:
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Position AI as a tool that removes friction, not people.
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Share real stories where AI has improved real work.
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Spotlight employee-led success stories to build credibility.
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Involve & shout about subject-matter experts to keep AI human-driven.
5. Practical steps to make AI a human multiplier
Start with pain points
The quickest wins come from tackling the everyday tasks your teams find frustrating, e.g., manual reporting, repetitive coding reviews, or time-consuming data entry. Freeing people from these pain points immediately shows how AI can add value.
Pick high-impact, low-risk pilots
Rather than starting with mission-critical systems, trial AI where the stakes are lower but the benefits are clear. Leaders at our roundtables emphasised that early “safe” wins help build confidence and momentum, creating internal champions for wider adoption.
Co-create with users
The best results often happen when the people closest to the work are involved in shaping the tools. They bring the knowledge to guide the AI, spot errors, and validate outputs, keeping solutions practical and trusted rather than forced from the top down.
Invest in training
AI isn’t plug-and-play. Teams need space and support to experiment, learn prompting techniques, and understand limitations. Upskilling builds literacy and helps remove fear, turning AI from a perceived threat into an everyday tool.
Measure what matters
It’s easy to get stuck on accuracy scores or technical benchmarks. We're seeing a lot of leaders track the outcomes that resonate with the business, time saved, fewer errors, faster delivery, or better customer experience for B2B businesses. These metrics help prove value to stakeholders.
The future of AI in teams
The overall conversation that we're seeing about AI, is that it doesn’t have to be about replacement. The organisations seeing the greatest gains are those treating AI as a partner to their people, amplifying capability, creativity, and resilience.
By positioning AI as a human multiplier, you’re not just adopting new technology. You’re future-proofing your team with stronger culture, quicker innovation, and good growth prospects.
💡 We help ambitious businesses hire and scale high-performing AI and Data teams. Explore more insights from our leadership community here.
If you're thinking of scaling an AI function or want to learn more about how our community are embedding the tools into their tech teams, drop us an email.
