AI Implementation: How Microsoft, Roblox, PwC, and Others Did It

2024 is, without a doubt, the year of AI in the Workplace.

From the moment ChatGPT was launched in November 2022, companies have increasingly undertaken efforts to bring Generative AI to their teams.

But just giving people a ChatGPT or Microsoft Copilot account isn’t going to magically deliver 40-50% productivity boosts across the board.

Significant AI change management measures are necessary, including conducting employee surveys, training, launch events, and ongoing support.

Rather than addressing general best practices, let’s look into how some companies have aced their AI implementations. 

This overview will be continuously updated by the team behind Lead with AI, the premier executive-level AI training and community. Last update: August 27, 2024. For submissions, please contact us.

Current cases covered:

• Apple
• Amazon
• BCG X
• Microsoft HR
• Morgan Stanley
• PwC Netherlands
• Roblox
• ServiceNow

Apple

As Apple is rolling out its own AI called “Apple Intelligence,” it makes sense that there isn’t a lot of insight into how the most valuable company in the world uses AI internally.

However, two projects are known (based on mostly rumours):

• Engineering Chatbot: Apple created an internal chatbot that some engineers call "Apple GPT." This chatbot requires special permission for employees to access, is used for product prototyping, and can’t be used to develop customer-facing product features
• AppleCare Support Tool: Apple is testing a ChatGPT-style generative AI tool called "Ask" with its AppleCare support employees. This tool generates responses to technical questions from Apple's internal knowledge base to speed up support replies.

Amazon

Through its AWS division, Amazon has been integrating generative AI into various aspects of its operations, transforming internal processes and customer engagement strategies. Here are some key takeaways from their approach:

• The Amazon Q Platform: Amazon developed Amazon Q, a generative AI-powered assistant designed for work purposes. Amazon Q can be tailored to a company's business and integrates with internal systems and data repositories. An example is the AI Sales Assistant, which is reported to save 35 minutes per summary, leading to a 4.9% increase in the value of opportunities created. 
• Strategic Model Selection: Amazon’s multi-model approach uses different generative AI models, including Amazon Titan and Anthropic Claude, tailored to the specific needs of different tasks. This flexibility allows for optimizing accuracy, response time, and cost-efficiency, ensuring that the right model is used for the right task.
• Mitigating Hallucinations and Ensuring Quality: Amazon is preventing AI hallucinations by implementing robust prompting strategies, specific and detailed instructions, and a comprehensive feedback loop involving automated metrics and human review. This multi-faceted approach ensures the quality and reliability of AI-generated outputs, making them more trustworthy for business use.

BCG X

BCG X, Boston Consulting Group's AI-focused division, has been at the forefront of integrating AI into its operations. Led by CTO Matt Kropp, it’s been driving AI adoption across the organization, focusing on enhancing employee experience and unlocking new growth opportunities.

Here are the key strategies BCG X used to implement AI effectively, as shared by Matt in our interview:

• Focus on Enhancing Employee Joy Through AI: BCG X is committed to using AI to minimize toil and maximize joy for its employees. By identifying repetitive, low-value tasks that AI can handle, it aims to free up employees to focus on more fulfilling work. This approach not only improves productivity but also enhances employee engagement and satisfaction.
• Co-Design and Community Engagement: BCG X emphasizes involving employees in the AI implementation. By co-designing AI solutions with the people who will use them and fostering a culture of peer sharing and community engagement (e.g., through hackathons and ambassadors), BCG X ensures better adoption and more effective use of AI tools.
• Discovery Sprints for Innovation: BCG X conducts "discovery sprints" to accelerate AI adoption and innovation. During these sprints, specific project teams are encouraged to explore and experiment with AI tools. The insights and techniques developed during these sprints are then shared across the organization, promoting a culture of continuous learning and improvement.
• Strategic Platform Selection: BCG X has strategically adopted ChatGPT Enterprise across the entire organization to empower its employees. This decision was guided by the need for a robust, general-purpose tool that integrates well with its existing infrastructure and supports the diverse needs of its workforce.
• Beyond Cost-Saving—Focus on Growth: BCG X's internal AI strategy is not solely focused on reducing costs. Instead, it views AI as a means to drive business growth by improving work processes, increasing output quality, and enabling new opportunities. This broader perspective allows BCG X to leverage AI for innovation and competitive advantage rather than just cost efficiency.

Microsoft HR 

Microsoft, maker of Copilot and backer of OpenAI, the company behind ChatGPT, has, of course, been working hard to roll out AI. 

In a fantastic case study shared by Global VP Chris Fernandez, we got a peek into how they pulled it off successfully:

• Human-Centered AI Adoption: Microsoft’s HR team emphasized the importance of keeping human judgment at the core of AI implementation. AI is treated as a tool that augments human decision-making, not as a replacement for it. Companies should focus on creating AI adoption plans that prioritize enhancing the human experience and maintaining a balance where AI supports, rather than overrides, human judgment.
• Empowering Non-Technical Employees to Create: Microsoft empowered HR professionals, who were not traditionally technologists, to become “citizen developers” using low-code platforms like Microsoft Power Apps. This democratization of technology enables domain experts to create tailored solutions without needing extensive coding knowledge. Companies can foster innovation by enabling employees across various functions to develop their own AI-driven tools with the help of low-code platforms.
• Iterative and Inclusive Innovation: Microsoft’s approach involved creating an innovation intake process and an AI community of practice, allowing ideas to be collected, prioritized, and refined continuously. This iterative process encourages cross-functional collaboration and ensures that AI-driven innovations are practical and aligned with business needs. Companies should establish mechanisms for ongoing innovation and collaboration, ensuring that AI developments are inclusive and meet the entire organization's needs.
• Focus on Practical Applications and Use Cases: Microsoft’s HR team used AI to address specific, practical challenges, such as automating routine tasks and improving employee interactions through AI-powered bots. This focus on practical use cases ensured that AI implementations delivered tangible benefits. Companies should start their AI journey by identifying specific areas where AI can provide immediate value and gradually expand as they gain experience and confidence.
• Commitment to Responsible AI: Microsoft grounded its AI efforts in its Responsible AI Standard, which includes principles like accountability, inclusiveness, and transparency. This commitment to ethical AI ensures that AI implementations are trustworthy and beneficial to all stakeholders. Companies should adopt similar frameworks to guide their AI initiatives, ensuring that AI is used responsibly and ethically across the organization.

Morgan Stanley

In June 2024, Morgan Stanley launched the AI @ Morgan Stanley Assistant. 

This generative AI-powered chatbot provides financial advisors with quick access to Morgan Stanley's intellectual capital. The tool's adoption rate has been impressive, with 98% of Financial Advisor teams using it.

CEO Ted Pick said these tools could save financial advisers 10-15 hours per week, allowing them to focus more on high-value activities like customizing investment strategies and deepening client relationships. 

PwC Netherlands

In a fascinating interview with HR Tech Director Marlene de Koning, we learned about how PwC Netherlands's clever approach to rolling out AI: 

1. Phased Scaling for AI Adoption: PwC started with a pilot of 300 AI enthusiasts and gradually scaled to all 6,000 employees in the Netherlands. This phased approach allowed for continuous learning, adjustment, and feedback, ensuring that AI adoption was effective and manageable. During this pilot, PwC launched three AI platforms: Microsoft Copilot, ChatPwC, and Harvey.
2. Integration of AI into Daily Workflows: PwC focused on embedding AI tools like Copilot into employees' daily workflows to ensure widespread and consistent use of AI. Integrating AI into familiar tools like Teams, Excel, and PowerPoint, PwC made it easier for employees to incorporate AI into their routine tasks. This approach highlights the importance of making AI accessible and relevant within existing work processes.
3. Identifying and Leveraging Specific Use Cases: PwC took a strategic approach by identifying specific use cases across the company where AI could provide substantial value. Examples include automating the summarization of client workshop notes and analyzing open comments from surveys. By focusing on practical applications that address real needs, PwC demonstrated the immediate benefits of AI, making it easier for employees to see its value and integrate it into their work.  
4. Cultivating AI Influencers: PwC identified and nurtured natural influencers within the organization using organizational network analysis. These influencers were critical in driving AI adoption by sharing their experiences, providing support, and encouraging others to embrace AI. This strategy underscores the value of leveraging internal champions to foster a culture of AI adoption.
5. Balancing Experimentation with Strategy: PwC emphasized the need for a clear AI strategy while encouraging hands-on experimentation. This balance ensures that AI initiatives are aligned with organizational goals while allowing flexibility to learn and adapt as the technology evolves. Companies should adopt a dual approach of strategic planning and practical experimentation to maximize the benefits of AI.
6. "AI in the Loop" Approach: PwC introduced the concept of "AI in the Loop," where AI supports human processes rather than replacing them. This approach helps address potential biases and ensures that AI enhances, rather than diminishes, the human element in workflows. Organizations can benefit from this mindset by ensuring that AI implementations are designed to complement and augment human decision-making.

Roblox

In an interview for our Lead with AI podcast, Roblox CHRO Arvind KC shared how they integrated Generative AI into their business:

• Integration of HR and Systems for Seamless AI Adoption: Roblox merged HR and Systems under a single leadership to create a unified, AI-driven employee experience. This integration allowed for smoother implementation of AI tools, ensuring that technology and people management strategies were aligned. Companies can learn that merging traditionally separate functions like HR and Systems can enhance AI adoption by creating a more cohesive environment where technology directly supports employee needs and organizational goals.
• Strategic AI Deployment in High-Impact Areas: Roblox focused on deploying AI in areas where it could provide immediate and significant value, such as engineering (which accounts for 80% of the business) and customer support. For engineering, Roblox opted for Github Copilot (#7 in our AI Top 100) and Saxon for customer service. This approach ensured that AI was effectively integrated into existing workflows, enhancing productivity without requiring significant changes to how work was done. Companies should identify specific, high-impact areas where AI can be most beneficial and focus their initial efforts to maximize early returns on AI investments.
• Balancing AI Hype with Realistic Expectations: While recognizing AI's transformative potential, Roblox emphasized the importance of setting realistic expectations for its impact. They avoided overhyping AI's short-term benefits, instead focusing on gradual, sustainable improvements. Companies can benefit from this approach by being patient with AI implementation, starting small, scaling over time, and maintaining a long-term perspective on AI’s potential to reshape their operations.

ServiceNow

Like Microsoft, ServiceNow sells AI services, which integrate with HRIS Software like Workday and other AI platforms like Copilot. 

In an interview with Fortune, the company's Chief Customer Officer, Chris Bedi, shared how they integrated through ServiceNow's internal processes, with over 25 use cases in production:

• Company-Wide AI Integration and Adoption: ServiceNow mandated that every department develop an AI roadmap, ensuring that AI was integrated into every aspect of the business, from software engineering to customer service. This approach led to 84% of the workforce using AI daily. Companies should consider a holistic, top-down approach to AI adoption, where every department is encouraged or required to explore how AI can enhance their operations.
• Impact-Driven AI Use Cases: ServiceNow focused on identifying and scaling AI use cases that delivered tangible business impact. They prioritized high-impact applications while discontinuing those that were less effective. This strategic focus on impactful AI implementations helps ensure that AI investments deliver measurable value. Companies should identify and scale AI use cases that provide the most significant benefit to their operations, ensuring a clear return on investment.
• Leadership and Employee Engagement: ServiceNow emphasized the role of leadership in setting the tone for AI adoption, making it clear that AI was a tool to enhance jobs, not replace them. They also actively measured employee sentiment toward AI tools, ensuring that the technology was genuinely helpful and embraced by the workforce. Companies should focus on clear communication from leadership about the role of AI, coupled with efforts to gauge and respond to employee feedback to foster a positive AI adoption experience.

Ready for your AI Implementation? Some guiding principles:

• Strategic AI Integration: All companies emphasized aligning AI tools with their business goals and processes. Whether through phased scaling, strategic platform selection, or focusing on high-impact areas, AI implementations were carefully tailored to enhance core operations without disrupting existing workflows.
• Human-Centered Approach: AI was implemented to augment human capabilities, not replace them. Organizations like Microsoft and PwC prioritized AI tools that support human decision-making, emphasizing the importance of keeping employees engaged and ensuring AI enhances rather than diminishes the human element in workflows.
• Iterative and Inclusive Innovation: Companies adopted an iterative approach to AI adoption, encouraging continuous learning and improvement. This included engaging employees in the development process, fostering cross-functional collaboration, and maintaining a feedback loop to refine AI applications over time. This approach ensured that AI implementations were practical, widely accepted, and continuously improved.

Need more to implement AI successfully? Check out our guide to AI change management.