"The biggest challenge isn't the technology—it's getting the business on board," declared Alvin Chau, leaning forward with the intensity of someone who has seen the future and is determined to bring others along. "From a technologist's perspective, the AI train is moving. If your executives aren't catching it, your competitors will."
As Chief Technology Officer at Frontier Dental, Chau delivered an extremely compelling call to action at our recent CIO ThinkTank Series on AI & Business Transformation. His urgency isn't just personal enthusiasm—it's backed by data showing 92 percent say they expect to increase their investment in AI over the next three years as organizations look to address and deploy new AI use cases.
For many IT executives in the audience, this call to action prompted an uncomfortable question: Are we moving fast enough?
For those interested in diving into the other articles in this CIO ThinkTank series, they have been listed here for your convenience:
Read on if you would like to learn more about getting the balance right between experimentation and strategic governance.
Rather than lengthy theoretical discussions about AI's potential, Chau advocates for showing, not telling. His approach centers on swift minimum viable products (MVPs) that demonstrate immediate value and engage with the business—often built in hours or days, not weeks.
Chau highlighted how he can build simple AI prototypes—like automated chatbots for customer inquiries or data classification tools—in hours.
"Suddenly, everyone wants to know what else AI could do for them."
This strategy serves multiple purposes:
Forrester's 2025 forecast validates Chau's approach, showing that 75% of firms attempting to create advanced AI architectures will fail due to the complexity and lack of expertise, highlighting the need for streamlined, iterative approaches like fast prototyping to reduce risks and improve scalability. As Chau puts it: "Speed is strategy when it comes to AI adoption." These insights stress that bridging gaps between technical and business expertise is critical for AI success, aligning with the idea that speed and collaboration are key to scaling AI effectively.
A spirited discussion broke out during the panel when another IT leader asked about overcoming leadership resistance. Chau acknowledged the very real concerns many executives harbor about AI's complexity, unpredictability, and potential regulatory hurdles.
"When I first show a CEO in early 2023 how Generative AI could summarize client feedback in real time, suddenly the conversation shifts from doubt to excitement," Chau recounted. "They start asking, 'What else can it do for us?'—and that's the spark we need."
Research from IDC reinforces this experience. Executive support is crucial, "rarely has a technology emerged with as much executive support, defined business outcomes, and rapid adoption as generative AI" revealing that companies with strong executive sponsorship for AI are more likely to see enterprise-wide deployment. For Chau, the ideal approach combines top-down mandates with grassroots experimentation.
Consider creating an 'AI Exploration Day' where every department could submit a challenge they wanted to solve, one executive explained. "We built six quick prototypes in a single day—from a tool that predicts appointment no-shows to one that analyzes equipment maintenance patterns. Four of those ideas are now in production."
It’s not just about technology; it’s a fundamental culture shift encouraging both leaders and employees to think, How can AI help me do my job more efficiently?
Having worked in regulated contexts, Chau encourages balances speed with security. Something he has considerable experience with his background in tackling many mergers and acquisitions. A data breach at a competitor could quickly sour executives on AI when sensitive information could be inadvertently exposed.
"I recommend starting with non-sensitive data," he advised. "Prove the value, then tackle more complex or confidential use cases once the right controls and AI governance are in place."
This approach directly addresses the growing concern around "shadow AI." A recent Cisco study found 48% admit entering non-public company information into GenAI tools, many which are unapproved AI tools at work—magnifying the risk of data leaks. Chau suggests central ai governance that's flexible enough to accommodate innovation while maintaining appropriate guardrails. In related discussions at the event one CISO shared that they had created a 72-hour approval process for AI experiments. “It needs to be fast enough that teams don’t go around it, but thorough enough to catch major security or compliance issues.”
Organizations like Paragon Micro play a pivotal role in helping businesses set up these flexible yet secure frameworks. With their deep expertise in IT governance and security, Paragon Micro assists companies in implementing AI solutions in a way that balances rapid innovation with necessary security protocols, ensuring that experimentation doesn’t outpace governance.
Like others at the ThinkTank, Chau sees a near future where AI becomes deeply embedded in workflows through tools like Microsoft 365 Copilot. "Soon, these capabilities won't be special—they'll be standard," he predicted. "The organizations gaining advantage now are the ones learning how different teams can leverage AI most effectively."
In discussions Chau shared how AI assistants can now draft emails, summarize meetings, generate presentation content, and augment creatives by generating initial design concepts to refine—all within familiar Microsoft tools that employees already use daily.
"The biggest value comes when AI becomes invisible," Chau noted. "Not a special project, but part of how everyone works."
"Many fear that AI technology will replace human jobs. In reality, AI will not simply eliminate jobs but rather redefine them, creating opportunities for those who adapt and embrace the technological shift.” Chau elaborated “The real risk lies not in AI itself but in failing to keep pace with its advancements. Those who proactively learn, upskill, and integrate AI into their workflows will thrive, while those who resist change may find themselves left behind in an evolving job market."
At the center of so much of this experimentation momentum lays business led agent development experiences like those accelerated by Copilot Studio. If you or your organization is trying to drive growth we strongly encourage having nominated team members join upcoming free Microsoft led workshops such like Copilot Studio in a Day workshop’s that give participants hands-on experience with expert instructors.
Chau's enthusiasm peaks when discussing emerging frontiers like emotional AI in robotics. With the global market for AI in robotics projected to exceed $100 billion in 2025, he sees early experimentation as laying groundwork for more ambitious innovations.
"Imagine a robotic assistant that can not only perform tasks but recognize when patients are anxious and adjust its approach accordingly," he speculated. "Or a warehouse robot that can analyze real-time camera feeds for anomalies using an on-board AI model. We're only beginning to see what's possible."
Chau concluded by returning to communities like the CIO ThinkTank's mission: "It's gatherings like this that create a collective learning experience. Let's keep building, experimenting, and sharing, so we can all ride the AI train together while we help others onboard."
As executives filed out, many were already scheduling meetings to kickstart their own rapid prototyping initiatives—evidence that Chau's message had found its mark.
In our next CIO ThinkTank article, we'll explore how one IT executive built a comprehensive data and governance foundation to scale AI across his organization: Building AI on a Solid Data Foundation: Governance and Value.(Coming Soon)
Subscribe for more insights on turning AI experiments into enterprise-ready solutions—and don’t miss our upcoming event, AI Agents at Work: Driving Value While Governing Risk, where we’ll dive deeper into practical, risk-aware strategies for harnessing AI’s full potential.
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