Lessons from Microsoft’s AI Centre of Excellence (CoE)

Forecasts are now indicating that the AI market will exceed $500 billion by 2024, Microsoft for obvious reasons recognised this imperative early on. Along with incorporating AI into its solutions, Microsoft has established an AI Centre of Excellence (CoE) to oversee the integration of AI technologies within the organisation. The CoE focuses on developing AI governance frameworks, conducting research on user experience, and ensuring the responsible use of AI. This effort includes robust lifecycle management for data, ensuring proper labeling and handling of sensitive information, and maintaining transparency to build trust among employees​.

With organisations of all sizes, all industries rapidly adopting readily available AI solutions, Microsoft’s CoE can provides a framework for businesses to harness AI’s potential. Key lessons include empowering the workforce, encouraging collaboration, prioritising valuable AI ideas, implementing responsible AI practices, and fostering a culture of continuous learning. As AI development accelerates, partnering with experienced AI consultants can expedite your journey to AI success.

According to a McKinsey report, 70% of digital transformations fall short of their objectives, often due to a lack of clear strategy and poor implementation. This underscores the importance of a structured approach, such as an AI Center of Excellence (CoE), to avoid costly missteps and maximise ROI.

Getting Started with your CoE: Defining AI Objectives

AI is all about empowering people to do their best work. The team at Microsoft takes this incredibly seriously, encouraging people to disrupt, innovate, and use AI creatively to seize opportunities. With that in mind, Microsoft started the process of building its AI Center of Excellence (CoE) by evaluating what the business and, more importantly, its people wanted from AI. Instead of simply adding AI solutions onto existing systems, Microsoft continually reexamines how things are done, seeking to find how they can drive creativity, transform experiences, and at the same time look after their people, their data, and the business. Microsoft’s CoE asks people to rethink their work with AI in mind, applying this approach at every level: each person, each department, and the organisation as a whole.

When asked what they’d like to achieve with AI, employees often touch on common themes, including:

• Simplifying and reducing mundane tasks to focus on productive and creative work.
• Finding information, summarising meetings and performing administrative tasks.
• Improving and informing creative work to produce deeper, more insightful results.

Rather than replacing people, AI engineers aim to empower them to achieve more. Therefore, it’s vital to include people in the process from the beginning. While your list might not be the same as Microsoft’s, it will likely include similar ideas, providing a great starting point for your AI strategy. Leaders at Microsoft aim to increase productivity, enhance well-being, accelerate work rates, and enhance human capabilities, ultimately all things that align with what their people want, which will not only drive productivity but improve employee well-being, too.

Structuring an AI Centre of Excellence

Microsoft employs experts across its business, including data science, machine learning, business intelligence, product development, and more, to define how to use AI. The team uses four key pillars to guide its work in planning, designing, implementing, and championing the company’s internal use of AI:

1. Strategy

The strategy pillar is all about examining AI as a way to transform rather than merely add to existing tools and processes. While the aim is to augment human capabilities, when it comes to the tools and processes themselves, it’s vital to be willing to start from scratch. To achieve this, the team examines every tool and process and tries to reimagine them with AI. The strategy piece begins at the top level of the business, ensuring any transformation resonates across the organisation. However, the team also actively welcomes ideas from every level, with no element of business processes off limits. The team evaluates the idea pipeline based on business value and implementation effort. High-value, low-effort ideas are at the start of the pipeline, helping to determine which projects should start first and when.

2. Architecture

The architecture pillar involves designing and managing the infrastructure, services, and data resources that power AI applications. The CoE ensures data is readily available, clean, and secure, leveraging existing IT assets wherever possible, and champions best practices and standards, promoting responsible AI development. Moreover, the CoE team allows developers to use their preferred tools and provides spaces for experimentation, facilitating rapid iteration and innovation while maintaining adherence to established best practices. Collaboration between architects and developers is also key. Together, they identify optimal architectural approaches, including microservices and cloud solutions, to ensure scalability. By building a comprehensive view of the infrastructure, the CoE lays the groundwork for seamless integration of new AI solutions.

3. Roadmap

The CoE roadmap focuses on the employee experience with AI. Extensive research ensures AI services and processes are not only effective but also accessible to all. The Roadmap team considers various use cases and interaction methods, including natural language interfaces and predictive interactions, to remove traditional input barriers. Ultimately, the goal is to transform how employees interact with products, creating a seamless and efficient workflow through simplified design.

4. Culture

Last but by no means least is the culture pillar. The CoE prioritises fostering a culture of responsible AI application development. This includes empowering employees by educating them and providing opportunities for them to learn the necessary skills to leverage AI effectively. The CoE culture team also promotes responsible AI practices throughout the organisation, including sharing best practices, educating employees on next-generation AI capabilities, and ensuring everyone understands the importance of using AI ethically and responsibly. Ultimately, the goal is to create a culture where employees can embrace AI as a tool for transformation while remaining mindful of its impact.

Building Your Own AI Success Story

Microsoft’s CoE serves as a great example of how businesses can build success with AI.  While still on their AI journey, the CoE equips Microsoft with a framework to drive innovation and positive change, empowering employees by fostering creativity, productivity, and growth.

To build your own AI success story, consider some of the key lessons from Microsoft’s approach:

• Empower Your Workforce – view AI as a tool to enhance employee creativity, productivity, and skill development.
• Encourage Collaboration – seek feedback from employees across the business on how AI can benefit their work.
• Prioritise Development – evaluate and prioritise the most valuable and feasible AI ideas to focus solution development.
• Responsible AI – implement robust governance and responsible practices across all AI initiatives.
• Continuous Learning – foster a culture of continuous learning and improvement to stay ahead of the ever-evolving AI landscape.

And remember, the pace of AI development is rapid. Partnering with an experienced AI development company adept in AI innovation consulting can provide valuable expertise and accelerate your path to AI success.

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