AI Transformation: A Proven Framework & Enterprise Success Stories

Artificial intelligence transformation is the most important trend in the enterprise world. Research from Gartner found that 77% of CEOs believe AI is “ushering in a new business era.” Similar research shows that 91% of C-suite executives plan to scale their AI transformations next year. 

While many of the world’s largest companies are investing billions of dollars in AI technology, other companies are still in the early stages of their transformation journey. They’re watching the technology mature and other companies experiment, planning for their own transformation in the near future. 

These leaders want to secure the same benefits from AI transformation, but they’re concerned with the high failure rate of AI projects (between 70-80%, according to the Project Management Institute). Organizations need a clear AI and digital transformation strategy to help them succeed and create an AI-first organization.

This strategy must be about more than tools and technology; it’s about a business's people, processes, and culture. 

This guide to AI and digital transformation will help leaders overcome common obstacles, generate excitement among employees, and build pilot projects that create lasting change and can be scaled across an entire organization. 

‍Introducing the ADKAR Change Management Model

‍

The Prosci ADKAR model was created by Jeff Hiatt in 2019. The acronym stands for:

• Awareness
• Desire
• Knowledge
• Ability
• Reinforcement

Since its recent launch, ADKAR has been adopted by numerous startups and global enterprises, including Microsoft, to achieve long-term organizational change.

While many change management models are available to executives, ADKAR is well suited to AI transformation because it focuses on helping businesses—and their employees—embrace new ways of thinking and operating in the workplace.

It also offers a clear roadmap for success, using clear goal-setting and a structured approach to help organizations embrace change and transform their workplace culture.

To succeed with the ADKAR model, leaders must accomplish each milestone before moving on to the next. This is a clear break from earlier change management models, which often failed to include measurable outcomes and a clear progression from one stage to the next. 

Finally, it’s important to realize that messaging is the key to ADKAR's success. This AI and digital transformation model emphasizes aligning leadership values with employee values, ensuring all levels of the organization are on the same page. The human element is the core of AI transformation, and the best companies leverage their employees as their strongest change element. 

This requires carefully framing AI adoption as a general-purpose tool and efficiency-improving technology, not as a threat to their jobs. AI is the equivalent of the internet or computer literacy skills in the late 1990s; it’s an emerging technology that will soon become a standard part of the white-collar toolkit, and workers can’t afford to ignore it. 

‍

Microsoft Uses ADKAR to Boost Customer Success

Microsoft was one of the first Fortune 500 companies to embrace ADKAR for change management. The tech giant used ADKAR to quickly diagnose customer pain points (and customer service bottlenecks), and quickly get employee buy-in for new processes and frameworks.

The Microsoft 365 Customer Success team used ADKAR to create awareness of new tools and features, gather customer feedback to understand communication gaps, and get their customer success staff, consulting teams, and end users on the same page. 

Ultimately, Microsoft successfully changed the narrative around its product offerings and “increase adoption of complex, cloud-based Microsoft 365 technologies.”

‍

Step 1: Awareness - Why AI Transformation is Necessary for the Modern Enterprise

Awareness is the first, and most important, step in the ADKAR change management model. That’s because organizations must first create awareness of the problem—and the need for change—among employees before change starts. This includes awareness among key stakeholders, mid-level management, and frontline employees.

Leaders can complete this stage by clearly explaining why the organization is embracing AI and how this new technology will help the business achieve its overall strategic goals. It’s not enough to say that “AI is the future.” This communication needs to be focused on tangible business outcomes.

Examples of tangible business outcomes include:

• Boosting operational efficiency — AI-powered programs can boost employee efficiency, automate boring manual labor, and improve productivity across the entire organization. This doesn’t replace employees; it makes them more efficient and valuable.
• Improving the customer experience — AI is a godsend for personalized customer experiences and customer service. AI chatbots and other tools can handle easy customer support inquiries and create a customized shopping experience, allowing humans to focus on edge cases and complex problem-solving.
• Enhancing Innovation — Current AI tools lack human ingenuity and creativity. But they’re great at automating boring workflows and crunching data to provide unique insights. This automation allows humans to focus on the type of creativity and high-level thinking they thrive with, like developing new products or planning for the future.
• Maintaining a Competitive Advantage — Your competitors are embracing AI right now. To stay competitive and maintain employment levels, organizations must adopt AI-driven technologies today. This will help your business thrive in AI and give employees job security in a tough job market. This is a strong message for stakeholders and internal leaders.

No matter which messaging leaders choose, it’s important to ensure that storytelling is personalized for current employees and stakeholders. Tying AI adoption to the company’s (and employees’) long-term financial success is also essential. 

Numerous companies have launched their AI transformation with employee messaging (aka awareness), including:

• Microsoft: Created awareness of how AI can improve workflows and free employees from boring tasks. “Using AI to streamline or automate repetitive, mundane tasks can allow your employees to dive into more complex, creative and ultimately more valuable work.” 
• Capital One: Tied emerging technologies and strategic business goals together in its messaging. “Today, AI and ML are foundational to how we continue to deliver value for our customers and our business.”
• NVIDIA: Launched the Deep Learning Institute to help companies tie business outcomes to employee L&D programs. “By developing needed skills, employees can make themselves more valuable to their organizations. And their employers benefit by embedding machine learning and AI functionality into their products, services, and business processes. 

Step 2: Desire - How Managers and Frontline Employees Should Embrace AI Transformation

Once you’ve generated awareness, it’s time to spark desire within employees. This critical step helps leaders create genuine support and excitement for AI transformations. 

It’s important to proactively address employee concerns and transform the narrative surrounding AI from one of fear to one of excitement. The most common employee fear around AI is fear of job loss. 

‍

To combat this pervasive worry, it’s important to frame AI as a job enhancer—and a tool that will make employees even more valuable to the organization. By developing in-demand AI skills, employees can improve performance, make themselves attractive leadership candidates, and secure their jobs well into the future.

One of the most effective strategies is identifying internal champions who can promote this narrative and proactively address employee fears. According to Forbes, “Success will belong to leaders who embrace AI without losing the human touch, instill trust in an age of uncertainty, and reskill their workforce for a future no one can fully predict.” 

Finally, transparency is the key to success in this step. Clearly explain the reasoning behind AI transformations to employees. Tie business outcomes and C-suite strategies to this new technology. In addition, employees should be involved in the decision-making process as early as possible. This will give them a sense of ownership in the process and confidence in the future. 

Here’s how some of the world’s biggest companies are creating employee desire for AI, and tying employee well-being with the new technology: 

‍

• AT&T: Launched its AI transformation with the headline “AT&T Expanding AI Across the Company to Support and Empower Our Employees.”
• Amazon: Created an AI-first culture by placing people at the center of its strategy. “AI is the most impactful technology advancement we’ll see in our lifetime, and its value and potential will only grow if employees and leaders know how to harness, build and create with it safely and responsibly.”
• Siemens: Encouraged employees to upskill with formalized L&D programs and AI learning paths. “Embracing people-centric digital re- and up-skilling is integral to this vision, where technology and people's potential meet to create transformative growth opportunities. 

‍

Step 3: Knowledge - Create an L&D Program for Successful AI Business Transformation

Now that leaders have created a sense of desire among employees, it’s time to give workers the knowledge they need to succeed. This step requires organizations to prioritize AI skills development and formalized learning and development (L&D) programs for employees. 

‍

An effective L&D program will teach employees the technical skills and AI tool knowledge they need to integrate AI into their daily workflows. 

The first part of this step is conducting a skills gap analysis to determine which skills employees currently possess and which AI skills they must develop to use AI day-to-day effectively. Based on these findings, HR and managers can create personalized L&D curricula for each department and skill group (technical, non-technical, and managerial).

Consider using a variety of learning approaches for success, including:

• In-person workshops
• Instructor-led virtual classrooms
• Self-paced learning modules
• Quizzes and tests
• Real-world assignments

In addition, companies can partner with local universities, Big Tech training programs (Google Cloud Training or NVIDIA’s Deep Learning Institute), or role-specific professional organizations (like PMI for project management or SHRM for human resources) to create specialized courses or offer recognized certificates. 

Here’s how Fortune 500 companies are sharing knowledge with formalized L&D programs:

‍

• Bosch: Integrated AI literacy into its corporate L&D programs and employee retention efforts. “Bosch is facing up to these challenges as a committed employer: we’re focusing on training and upskilling as well as on intelligent technology that makes associates’ work easier.”
• IBM: Launched an AI chatbot named IBM Watson to train employees and upskill for the AI era: “AI won’t replace people—but people who use AI will replace people who don’t.”
• Intel: Created the AI for the Workforce program to launch new products and train new industry employees on emerging AI technology. “The AI labs will provide students with more access to AI tools and resources, equipping the future workforce with the skills needed for the jobs of tomorrow. 

‍Step 4: Ability - Tie L&D Outcomes to Real-World Workflows and Pilot Projects

Now that employees have developed foundational AI knowledge (and the confidence to use AI in the real world), it’s time to connect the L&D curriculum with real-world projects and workflows. This provides workers with the ability to integrate AI into their day-to-day life.

One of the most effective ways to tie L&D programs to organizational outcomes is by allowing participants to create pilot AI programs for their departments. These are small-scale projects launched in controlled environments. They allow workers to apply their newfound skills to pain points in their jobs. 

Pilot programs should be narrowly focused and applied to a single business problem with clear objectives and success metrics. Once employees have demonstrated success, the organization can scale these AI transformations to other teams and departments. 

This approach helps solidify the learnings from AI training. In addition, it creates a sense of ownership among employees and is the first step to creating an AI-first company culture. Here are some companies that have made AI-first a standard business practice.

‍

• Shopify: The company went beyond training—AI use is now expected from every employee at the organization. “At Shopify, using AI effectively is no longer optional. It’s a baseline expectation for every employee, no matter their role.” 
• Colgate-Palmolive: Encourage employees to tackle AI pilot projects to demonstrate immediate value. “We didn’t want to simply dabble in various aspects of generative AI—it’s all about driving value. We’re focused on a few key enterprise priorities with this technology.” 
• Liberty Mutual: Partnered with MIT to create pilot AI programs that demonstrate AI value in insurance. “AI tools and technologies are reshaping industry, and insurance is no exception…[we] look forward to leveraging AI research to identify, develop, and ultimately operationalize several transformational AI-enabled solutions.”

‍Step 5: Reinforcement - Create Lasting Change by Integrating Learning into Daily Workflows

The final step in the ADKAR process is reinforcement. This solidifies the company’s AI-first culture and transforms small wins into a new way of thinking. 

Reinforce AI successes by celebrating small wins. Congratulate and reward employees who launch successful pilot projects. Consider tying these wins to performance bonuses, annual raises, and promotions. Use internal newsletters and win wires to announce these achievements to the company.

In addition, leaders can create a culture of innovation by scaling pilot projects into larger initiatives. Employees love to see their efforts celebrated (and recognized company-wide). This encourages other workers to innovate and build their own success stories. 

Here are a few examples from successful enterprises that have scaled AI pilot projects into full-blown AI-powered strategies. 

‍

• Mastercard: Rapidly expanded the size and scope of its AI pilot projects for fraud detection after early success. “In the last 12 months, we’ve stopped over $20 billion worth of fraud” using AI for decision management. 
• Mayo Clinic: The healthcare organization has gone all-in on AI for operations after successful pilot projects. “Mayo’s willingness to invest in these solutions [like robotics for hospital operational tasks] builds on its pre-existing robotic pilot programs.” 
• Walmart: Walmart launched a pilot program for AI inventory management in 2020 at 100 stores, before scaling the program worldwide in 2023. “By utilizing a scalable and flexible ML platform like element, our teams can continue to experiment with capabilities that enhance cost savings and efficiencies, promote the development of best-in-class tools and reduce time to market for AI solutions.”

‍

By implementing the five-step ADKAR model, executives can achieve successful AI transformations and turn their company into a truly AI-first company that’s capable of using emerging technology to develop a competitive advantage, improve efficiency and innovation throughout the organization, and remain on the cutting edge of enterprise technology in the AI era.