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AI Workplace Innovation: Opportunities, Challenges and the Road Ahead

COPILOT INSIGHTS SERIES #1

The uptake of AI for workplace innovation amongst small to medium sized businesses in the APAC region is happening at a rapid rate. Partners have significant opportunity to respond to demand, yet also must decide where to invest for profitable, sustainable AI-focused practice builds.

To help our partners make sense of the AI opportunity with Copilot, we’ve teamed up with one of the region’s leading advisors on the Future of Work.

Dr. Sweeney is a recognised authority on Microsoft and a respected advisor on technology strategy for Government and business.

In this series, Dr. Sweeney offers partners an independent take on capturing AI-driven business growth with Copilot.

Watch the video for highlights and dive into Dr Sweeney’s expanded perspective in the full article.

From emergence to AI awareness

One of the best parts of my job is exploring cutting-edge technologies as they emerge and evolve. It’s fascinating to study what’s already hitting the market while also peering into what’s still in the labs, waiting to disrupt how we live and work.

One of the biggest misconceptions I’ve encountered in my years of research is the idea that new technologies emerge out of nowhere, seemingly overnight. People often say, “Wow, this just came out of the blue!” But the reality is very different.

Over 25 years ago, I helped a friend start an AI company. Back then, we called it computational linguistics, a field that eventually evolved into machine language translation and, now, the generative AI tools everyone talks about.

The point being that technology doesn’t just explode onto the scene; it progresses steadily and predictably. Sure, that pace accelerates, but it’s not chaotic or random.

Artificial intelligence (AI)—the hottest topic in tech right now—is no exception.

Current AI tools like Microsoft’s Copilot, result from decades of groundwork. The seeds of what we’re reaping today were planted a long time ago.

I’ll say this much: the name “Copilot” is brilliant. It perfectly encapsulates what AI should be—an assistant, not a replacement.

Copilot is simply that; a tool that helps humans work better, faster, and smarter. Microsoft has done an excellent job of branding this concept.

Why is AI taking off now?

The answer comes down to economics.

Over the years, the cost of training and running AI models has dropped significantly.

This has allowed companies like OpenAI and Microsoft to build and deploy massive AI models—tools that they can now afford to offer at a relatively low cost.

AI FOMO vs Business Outcomes.

In terms of AI and harnessing it for workplace innovation, we’re seeing a lot of pilot projects with Copilot, particularly within the Microsoft 365 suite.

However, the expansion of these Copilot projects has been slower than many expected. Why?

Based on feedback I am hearing, these are some of the common factors:

Microsoft —and the industry as a whole—has struggled to show organisations how to use these tools effectively and integrate them into their workflows.
The technology is immature. Tools like Copilot are still clunky and require a lot of manual instruction entry. Although this is changing – and quickly – current systems can be difficult to master even for technical users.

Unclear outcomes. While companies are impressed with the results of their proof-of-concept trials, they’re struggling to connect those results to clear, tangible business outcomes.

In other words, once the initial excitement and rush-to-adopt subsides, organisations are asking, “where’s the value?”

This is a question that partners need to answer with confidence.

While the trend for companies to continue investing in AI is clear, there’s a key that must be turned to take the SMB market from niche projects to scaled implementations.

That key is in how partners articulate and prove that Copilot directly contributes to the achievement of critical business and/or IT objectives.

Trust as an AI Adoption Barrier

One of the biggest challenges faced in driving AI adoption is trust—or, more accurately, the lack of it.

Distrust of AI is widespread, and it’s not just limited to concerns about the technology itself. People are worried about how AI will impact jobs, privacy, and organisational decision-making processes.

However, an interesting correlation emerged in a recent study I conducted with over 1,000 Australian workers.

The data shows that people’s trust in AI and overall perception of its benefits were strongly linked to whether they had direct experience using AI tools like Copilot in the workplace.

In other words, familiarity breeds trust. The more people use AI and see how it can help them, the more likely they will be to embrace it.

This finding highlights an important takeaway for organisations: if we want to build trust in AI, we need to increase exposure to it.

That means giving workers access to these tools and opportunities to experiment, learn, and experience their value firsthand.

The frontline will need to see – in real world terms – how saving time, improving accuracy, or unlocking new revenue streams provides specific benefit to their roles and responsibilities.

It sounds obvious, but the data clearly shows the importance of exposure.

Building Trust and Demonstrating Value.

To overcome frontline resistance and encourage broader adoption, we need to work with customers to build internal trust through transparency. This means encouraging business leaders to be upfront about where the business believes it can deliver measurable benefits to customers and employees alike.

It’s not enough to say, “AI will make your life easier.” It will involve bringing employees in on plans earlier rather than later and being open about how AI adoption may change established norms in the business.

Another trust building factor is having open dialogue on fair, ethical and responsible use of AI.

There is a growing body of evidence around how AI can have negative – if unintended – consequences that can cause harm.

Employees, customers and shareholders alike want confidence that AI will not be misused.

For partners, these emerging and important operational policy considerations represent new fields for advisory and consulting engagement.

Looking Ahead

As we look to the future, I’m optimistic about AI’s role in the workplace. Tools like Copilot are just the beginning. The next generation of AI agents will be more intuitive, powerful, and seamlessly integrated into our workflows. But for this vision to become a reality, we must address the challenges of trust and value head-on.

The good news is that the momentum is already there. Organisations are continuing to invest in AI, and its benefits will become more apparent as the technology matures.

I firmly believe that the future of work is one where humans and AI work together—not in competition, but in collaboration.

For Crayon’s partners, my main advice is not to wait for AI tools to become perfect; they never will. The sooner you begin experimenting with AI and integrating it into your workflows, the sooner you’ll start to see its potential.

In my next post for this series, we will explore the near-term future and how AI automation and orchestration creates new opportunities for partners, as the technology evolves from prompt-forward generative AI to agents.

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AI Automation: taking Copilot beyond the prompt

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About the Author

Dr. Sweeney is a principal advisor and industry analyst at IBRS. He is a recognised thought leader in Future of Work, digital innovation, workforce transformation, and organisational change strategy. His fields of expertise include Microsoft, Google, AWS, VMware and Citrix.