Editorial
Research Report
The AI Transformation 100: Concrete Ideas for Fixing How We Work
Recent Avanade research found that 85% of mid-market organizations worry that they risk losing their competitive edge if they don’t accelerate AI adoption.
They’re not wrong.
But achieving business value and market differentiation with AI requires balancing technology change with behavioral change. Yes, modernize your infrastructure. Yes, fund use cases that maximize efficiency. Yes, identify what can be scaled for impact. But don’t ignore the cultural shift that must be nurtured. Get your AI investment right with both a platform- and people-anchored strategy.
Table of Contents
- Building a Strong Digital Core to Enable Scalable Growth
- Empowering a Leaner, Smarter Workforce
- Creating a Strong Governance Framework
Building a Strong Digital Core to Enable Scalable Growth
Let’s start with the “easy” part... easy because the technology will ultimately do what we tell it to do.
To equip teams to harness the growing capabilities of AI, organizations must upgrade their core infrastructure to support AI-ready workloads. AI requires fast, reliable hardware to run efficiently. Modern, thoroughly tested platforms will be essential for systems to operate smoothly. Additionally, scalable cloud connectivity will allow organizations to expand based on their unique computing needs. Ensuring systems can communicate effectively through enhanced data integration is also critical, as AI depends on this information to deliver advanced, real-time analytics.
The good news is that incorporating AI into an organization’s workflow doesn’t require a complete overhaul of existing legacy systems, since many can often be reprioritized for AI projects. The right systems integration partner will help you evaluate your current platforms for flexibility and modularity. The right partner will also help ensure that digital investments align with broader business priorities around AI, rather than stand as isolated modernization efforts. This is important because AI should serve as a business-wide enabler, with many teams benefiting from it, not siloed within individual departments.
Related Article: Your Board Wants AI ROI. Here’s Where to Start.
Empowering a Leaner, Smarter Workforce
Whereas technology will do what we tell it to do, humans are often a different story, and there’s much to consider along those lines. Worry, frustration and doubt all inhibit user adoption and are roadblocks to a successful AI program. Your teams should feel that technology will amplify their impact, not replace them. For instance, implementing automation and AI can reduce time spent on lower value tasks such as data entry, scheduling or processing invoices and expenses. This allows employees to focus on more strategic activities that realize benefits across departments.
However, as much as AI is designed to make work easier, the learning curve is real: employees can’t be expected to adopt these tools instinctively. Organizations that want to see meaningful ROI from AI investments must first create upskilling programs that help existing teams adapt to new tools, workflows and AI-assisted decision-making. Research shows that nearly 8 in 10 mid-market organizations are increasing their investment in AI training.
A thoughtful training curriculum will help employees understand that building AI skills is an ongoing journey, one that’s supported by consistent feedback loops that reveal what’s working and what’s not for team workflows. Internal champions play a key role in advocating for new tools and helping guide the transition when older solutions need to be phased out. Ultimately, long-term success depends on fostering a culture of agility. Team members should be expected to pilot, iterate and evolve AI use cases in tandem with daily operations, anchored by a shared commitment to learning and progress.
Finally, as new hires are onboarded, and teams shift capacity thanks to automation, roles and responsibilities should be adjusted to reflect the new blended human-machine model of work. This means emphasizing critical thinking, oversight and creativity — areas in which the human element adds unique value. Ultimately, it's this human vision, supported by AI, that will propel organizational progress, turning resistance into enthusiasm.
Creating a Strong Governance Framework
Closely tied to a smarter, more empowered workforce is the right governance model to help them use AI responsibly. The fast pace of AI advancement means that even well-meaning deployments can go awry without clear boundaries and safeguards. Only 39% of mid-market businesses say they have a complete set of guidelines in place for responsible AI. Without guardrails, innovation risks outpacing accountability.
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Establishing a strong AI governance framework is critical to ensuring responsible AI (RAI) use, especially as a single data leak or inaccurate output could undermine customer trust. These frameworks should address core principles such as data quality, bias mitigation, transparency and security. RAI policies help employees confidently utilize AI while navigating privacy requirements and regulatory standards. As AI models can also reflect or amplify bias, it’s essential to train them using high-quality, diverse datasets. Access should also be carefully managed; companies can establish role-based controls to AI tools and data to ensure sensitive information is used appropriately across teams.
To strike the right balance between experimentation and risk management, IT, legal, HR and business leaders should all be involved in AI oversight. Their input helps safeguard the enterprise as it forays into this new, unprecedented technology. Encouragingly, 42% of mid-market leaders say they are planning to develop RAI guidelines to inform their internal data and Al practices, and that’s definitely a step in the right direction.
AI is evolving rapidly, and getting your investment right will require not only integrating new tools, but developing a workforce that feels excited about and confident in using them.
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