The Trust, Experimentation, and Leadership Behind Impactful AI Adoption

AI has become ingrained in every industry. Some organizations are all-in. Many want to be. Few know where to start. Even fewer know how to start responsibly.

Giant’s client base varies widely in volume, industry, and audience, but they all share a hunger to adopt AI and adopt it well. Whether we’re talking to regional technology providers, nationwide member associations, or globally reaching brands, we’re seeing leaders across the board who understand the necessity of implementing AI into their workflows but lack the context to determine where it belongs. 

We sat down with Lucas Mistelske, Giant’s Chief Experience Officer and a long-time technology executive, to learn how businesses are approaching AI.

KEY TAKEAWAYS

• AI is changing how businesses compete—externally and internally. 
• Lasting AI adoption begins with people and processes, not platforms. 
• Leaders who experiment openly build teams that innovate confidently. 

How are businesses approaching AI conversations with agency partners?

The conversation is often twofold: leaders recognize AI is changing how audiences discover, evaluate, and interact with content, and that engagement strategies need to shift accordingly. At the same time, they’re eager to explore how it can strengthen internal workflows, supplement marketing and lead generation efforts, and deliver elevated, efficient employee experiences. They’re looking to their agency partners for guidance on both fronts.

External: The Evolution of AEO

More than 50% of Google searches now display an AI Overview—and according to a 2025 Pew Research Center study, users are far less likely to click on search result links when one is present. The result is a fundamental shift in how organizations earn visibility. After all, having a top-ranking SEO (Search Engine Optimization) page doesn’t mean much if no one scrolls past the AI summary to see it. 

Now, organizations are focusing on how AEO, or Answer Engine Optimization, fits into their digital strategy. Where SEO prioritizes short keywords and phrases, AI-generated summaries are more conversational, favoring longer-form responses that can stand on their own to answer a specific question. 

If competing for top-ranking search results was intense, earning a place in an AI summary is cutthroat. But it’s also an opportunity for pages that lack link authority to earn more visibility. As the experts at SEO Crawl put it, “AI Overviews frequently cite pages from positions 4–20 and beyond. This makes AI Overview optimization an opportunity for pages that have strong content but haven’t yet built the link authority to compete at the top of traditional results.”

So, while the technology has evolved, the fundamentals haven’t. Your audience still wants authoritative content that’s relevant to them, delivered by an expert with a clear point of view. Organizations consistently producing and publishing that content will continue to earn visibility, whether audiences discover it through a top search result or an AI-generated summary.

Internal: Workflow Improvement

While the conversation often starts with how AI can be leveraged for clients’ marketing, communications, and lead generation activities, it usually turns into something bigger: how can we ensure we’re leveraging it in a way that our customers, employees, and partners can trust? 

This is the part of the conversation I get most excited about. Some business leaders are thinking big picture and charging ahead full speed: they want AI implemented across every aspect of their organization, they’re developing their own internal tools, and they have the time, capital, and resources to fast fail. However, most leaders are being driven by necessity and value. They want to use AI to break down their biggest roadblocks and inefficiencies, but they may not know what those roadblocks are or where to start.

The latter is where active, involved leadership thrives. If you simply set a standard that everyone has to implement AI without providing any guardrails or testing the tools yourself, you’re simply requiring your employees to do more without demonstrating any real value. Instead, I encourage our clients to start from a place of wanting to improve the employee experience. Understand the friction your employees are working against, and collaborate with them to find ways AI can be used as a functional workstream mechanism to reduce friction. 

How can leaders take an active role in AI adoption?

Business leaders are the example and use case for AI adoption. If you’re in the weeds testing and implementing tools into your own workstreams—and being transparent when an experiment doesn’t work—I’ve learned that your employees will follow suit. So, be the example. Give your people the space to experiment and the trust to fail.

While you don’t need to have all of the answers, you do need to set the tone and conditions for responsible experimentation. The road to adoption looks different for every organization, but we encourage our partners to follow a few simple principles to ensure transparency and trust throughout their journey: 

1. Set standards for internal AI exploration and adoption. Most of us aren’t handling nuclear codes or classified government intelligence, but we still need to be cognisant of the regulations set by our industries, customers and partners. Set clear expectations for where and how AI should or should not be used, and hold yourself to those same standards.

2. Communicate with your internal team. Ethical AI adoption starts with clarity, transparency and understanding. Engage in open, honest conversations to learn which workstreams are holding your people back: where do they feel the most friction in their day-to-day? What lower-value work is keeping them from producing high-value work? 

3. Break down the workstream to solve for the point of friction. You may not be able to automate the entire workstream—but chances are, the entire workstream isn’t the problem. By gaining a clear understanding of every task involved in execution, you can identify exactly where your team is losing time, energy, and value.

4. Look to the vendors and partnerships you already use. Many of the major players in the digital marketing space are testing and deploying their own AI agents and tools. Start with the platforms you know and trust—they may already be addressing your specific pain points.

5. Explore, experiment, and be open to fast failures. Unless you’re a surgeon, the stakes of experimenting are probably lower than you think. Move with meaning, and accept that some tools may not work—but don’t let it hinder your desire to try again.

The best results come when you lead by example, giving your people the space to experiment and the trust to fail.

What does practical AI exploration look like in practice? 

Giant is a dynamic business, and we learned there’s no one-size-fits-all approach that works for every department or role. At the same time, we want to keep a close pulse on what, why, and how our teams are exploring—so we created an internal “Nerd Collective” comprising experts across our digital, creative, and client-facing departments. 

This inquisitive cohort meets every few weeks to dissect, share insights, and show off the latest tools they’ve been working with. Some are focused on new tools being rolled out by platforms and applications they already use, while others are innovating to build and code their own AI assistants and automated workflows. 

Has your team found success with any of these tools?

Yes! One of my favorite Nerd Collective success stories came from our graphic design team. When our designers build a web prototype, they’re meticulously creating and coordinating countless minute components: graphic overlays, calls to action, fonts, color palettes and so much more. Historically, they had to spend hours packaging and labeling each component before sending the final version to development…until a platform (that they already used and trusted!) introduced an AI tool that could do it all with a few clicks. Now, our designers only have to double-check the accuracy of the final web design package, and they get hours back to put toward the real, value-driving creative work they’re here to do.

What’s been the most rewarding aspect of leading a company through AI exploration?

The new AI frontier is vast. It’s daunting. But it’s also an exciting opportunity to connect with your team and your work on a deeper level. As we pursue the most practical, value-additive use cases across our departments at Giant, we’re uncovering friction points we never knew existed—and therefore, had never been able to fix. As a people-focused leader who is passionate about improving the experience for employees and clients, I’ve found those discoveries to be the most rewarding.