Who’s the New Guy?

AI isn’t a magic wand or silver bullet. It’s your newest team member, one that happens to be lightning-fast, infuriatingly literal, and prone to making things up when confused.

Last month, the Catalyst Leadership Trust assembled to discuss our partner Samudra Group’s AI Odyssey report, diving into how organizations can actually thrive in the age of AI. The session brought together C-suite executives, industry leaders, and transformation experts to uncover what’s really working.

The consensus was clear: to realize AI’s value, treat it like what it increasingly resembles: a new type of employee. That means onboarding it with intention, structure, and clear expectations.

Set Up AI’s Workspace

For AI, this isn’t about desk assignments. It’s about ensuring the data your AI will use is actually usable. If your data systems are chaotic, AI will be confused. When confused, it hallucinates or shuts down entirely.

The reality: AI governance adds 10-20% to traditional oversight budgets. Factor this into your business case now.

Action: Start with one clear use case, like customer service for a single product line. Build solid data architecture, access controls, and tagging around that specific workflow.

Give AI a Job Description

You wouldn’t hire an executive and say, “figure it out.” Yet that’s how many companies deploy AI, without defined use cases, boundaries, or success metrics.

Accenture got this right with their AI-powered Proposal Builder. Clear mission: reduce proposal creation time from hours to minutes while improving customization. With that focused scope, they could set goals and coach the system toward success.

Result: 50% productivity boost with measurable improvements in brand consistency and personalization.

Action: Define what AI owns and what it doesn’t. Set boundaries, deliverables, and dependencies just like any critical role.

Put AI on Cross-Functional Teams

AI works best as a collaborator, not a solo performer. Research shows human-AI teams outperform both humans alone and AI alone by 12-17%.

Colgate-Palmolive pairs product teams with AI systems to review market data for new opportunities. The humans aren’t just auditing, they’re actively shaping outputs. The result? Broader innovation funnels and faster time-to-market, with zero AI disasters.

Action: Reconfigure teams so AI isn’t sitting alone in a tool stack. Assign it to cross-functional units where humans validate, improve, and direct its work.

Measure AI Like You Measure People: with KPIs

ROI and internal AI adoption rates are good metrics. But, if AI is an employee, you should measure performance with business contributions such as output quality, accuracy, and speed of service.

Swedish fintech Klarna integrated AI across innovation teams with shared KPIs. Results? 60% faster go-to-market cycles and 59% faster innovation rates.

Action: Set performance metrics that measure real business impact. Evaluate and iterate like you would with any high-potential hire.

The Real Transformation Ahead

AI is powerful, but it’s not plug-and-play. Organizations that onboard AI with the same rigor they apply to executive hires will see the real returns: smarter teams, faster execution, and better outcomes.

But here’s what we’re learning: the technical implementation is just the beginning.

In a recent workshop with healthcare executives, we asked a simple question: “What percentage of AI transformation is cultural versus technical?” The overwhelming response: 80% cultural, 20% technical.

So while you’re onboarding AI as your newest hire, ask yourself: How will you help your existing team embrace this new colleague? How will you maintain customer confidence as AI becomes part of their experience? And most critically, how will you ensure this transformation accelerates your boldest strategic goals rather than just adding another layer of complexity?

#AITransformation #ExecutiveLeadership #OrganizationalChange #Innovation #FutureOfWork

You’ve spotted the AI opportunity. You’ve run the experiments. You’ve seen what’s possible. But now you’re hitting the real challenge every Catalyst knows: getting everyone else to see what you see.

Maybe you’ve been experimenting with prompt engineering, using automation to eliminate repetitive tasks, or testing tools that help you move faster with less friction. You saw the opportunity and leaned in. That’s what Catalysts do.

But influencing peer buy-in, getting other teams on board, or securing funding to roll out enterprise-wide solutions is frustrating. The key isn’t convincing them AI is amazing, it’s meeting them where they are and showing them what matters to them. Here’s how:

1. Lead with Outcomes, Not Enthusiasm

Non-Catalysts don’t always want to try new tools, but they do get inspired by the results those tools drive. Instead of telling everyone how effective your AI experiment was, show them what it achieved.

Did you improve email outreach? Reduce product development time and QA overhead? Decrease customer care call times while increasing NPS? Make it tangible. And if you want to make Finance sit up and take notice? Quantify the benefits with money made or time saved.

Don’t say “Our AI tool is incredible!” Say “This saved me 8 hours last week. Here’s exactly what I did with that time instead.

2. Offer Safety to Experiment Together

Some of your peers are curious about AI but afraid to admit what they don’t know. This is where your Catalyst mindset can shine. Share your failures as well as successes and encourage them to experiment.

Share what you’ve tried. Be honest about what didn’t work. Offer to experiment together; no judgment. Normalize the idea that you’re all learning together and create a safe space for it to happen.

3. Be a Trusted Sensor for Your Execs

Executives are feeling the pressure to “do something with AI,” but many aren’t sure where to start. This is your chance to move your AI breakthrough from experiment to enterprise.

One member of our Catalyst Leadership Trust calls this a “radar buoy”—being closer to the front lines and spotting opportunities others miss. If you see an AI use case that could help the company pivot, don’t keep it to yourself. Share it in a way that’s clear, relevant, and aligned with business priorities. (Hint: see Tip #1 to frame your thoughts.)

4. Model the Human Side of AI

You already know AI isn’t just about replacing people, it’s about augmenting your impact. Help others see this reality: show how you’re using AI to free up time for deeper thinking, better collaboration, or more strategic work.

Another Trust member shared their own great example: using AI to personalize sales emails to prospects, a job that used to take hours, now accomplished in minutes. As a result, his sales team has more time to spend in detailed discussions and relationship building with interested people, something AI can’t do. One good example helps head off fear and builds trust in how this technology can support, not threaten, your colleagues.

Catalyzing AI Innovation on the Front Lines

This is classic Catalyst territory: you see the future, you’ve tested the path, and now you need to light the way for others. The organizations that win with AI won’t be the ones with the best technology; they’ll be the ones whose Catalysts successfully brought everyone along for the transformation.

As a Catalyst, you’re already there. Now help everyone else come with you.