Introduction 

Organizations of all sizes and types across the globe are implementing AI solutions. According to McKinsey, business adoption of AI more than doubled in the five years between 2017 – 2022, with more than half of all companies using some form of AI. In 2023, McKinsey reported that 33% of organizations across all sectors had adopted the use of generative AI regularly in at least one function. Spending on AI is projected to exceed $300b in the next two years, with organizations focusing primarily on enhancing productivity and efficiency through this set of technologies. This means that AI will become embedded into every function in every kind of work environment. At the same time, software companies are increasingly embedding AI into their applications, resulting in more integrated solutions. 

As many organizations are still trying to figure out the strategy and governance to introduce generative AI into their processes and workflows, approximately 20% of workers report using ChatGPT at work, with 31% of younger workers reporting using it, according to Pew Research Center’s recent study on the adoption of ChatGPT. Gen AI is gaining use by workers at a pace dramatically faster than other technologies previously studied. Executives overseeing corporate AI adoption strategies and policies now need to try to catch up with the actual adoption and usage of Gen AI by workers. (King)

While this statistic refers only to Chat GPT or generative AI adoption, it should be noted that, throughout this paper, by “AI,” we are referring not only to generative AI but to all forms of artificial intelligence technology. We recognize that forms of AI technology have been used by businesses for decades, but given the trends stated above, we assert that with the most recent advancements in AI technology development and recent adoption trends of generative AI, organizations should think comprehensively and strategically about how AI can and should be used in their organizations, using a human-centric approach to adoption and integration.

In January, the Team Flow Institute Fellows published their first paper, Envisioning the Future of Human Work in the Age of AI: The 2024 Forecast and Research Agenda. This new paper, How to Prepare for Successful Integration of AI to Achieve Business and Human Success, builds upon that work, offering practical guidance to organizations on how to prepare to successfully implement AI by rethinking the role of AI in the workplace using team flow principles. 

While many organizations are focused on the potential productivity and efficiency gains and cost savings that using AI can provide, the Team Flow Institute Fellows recommend rethinking and reframing the role that AI can and should play in the workplace, focusing on: 

• How AI technologies can augment and elevate human work rather than just automate tasks
• Empowering employees rather than replacing them and placing more value on human work 
• Measuring “progressivity” as opposed to productivity as a key success metric 
• Envisioning new opportunities and possibilities with the addition of AI technology, rather than just adopting a new technology and conducting business as usual
  
  

In addition to this rethinking and reframing of the role that AI can and should play in organizations and placing more value on the role that humans play, the Team Flow Institute Fellows recommend embracing the Team Flow model as the foundation for this preparation, fostering a culture of collaboration, communication, and innovation. This approach establishes the foundation for an ethical governance framework for AI integration and development within organizations. The Fellows stress the importance of implementing AI within a larger digital and business transformation strategy, supported by governance, training, skill development, and enablement, investing in intensive change management and change communications, and an assessment of organizational design, structures, teams, roles and responsibilities, and capabilities. In addition to these recommendations, the Team Flow Institute Fellows have developed a set of 20 questions that organizations should ask as they implement AI. 

We hope that thinking about this approach, asking these questions, and considering these actions will enable organizations to be successful as they seek to position themselves at the forefront of AI adoption to achieve business and human success.

Jennifer McClure, Editor
Senior Fellow & Advisor
Team Flow Institute

Reframing the Role of AI in the Workplace 

From the Automation of Tasks to the Augmentation of Human Work

A fundamental step that organizations should take to prepare for successful integration of AI to achieve business and human success involves leaders reframing the way they think about the role of AI in the workplace –  focusing on how AI can augment, rather than just replace or automate, the current processes and tasks performed by people and teams.

One aspect of this change in mindset is the concept of augmented intelligence over artificial intelligence. Augmented intelligence is a design philosophy emphasizing enhancing human intelligence rather than replacing it with AI. Augmented intelligence focuses on AI’s assistive role and the belief that technology is designed to enhance human intelligence, not replace it. The goal of augmented intelligence is to foster a collaborative partnership between humans and machines, where the rapid processing abilities of machines complement human decision-making and creativity. (Debogovich) 

As AI’s capabilities continue to be developed and adoption continues to grow, some tasks will be fully automated, and some will be augmented. The key is knowing which should be automated and which should be augmented. Just because AI can do something doesn’t mean it should. (McClure) 

The challenge is that, as we collect more data and machines improve, more augmented tasks will be completely automated. Even some human decisions and aspects of creativity can and probably will be automated in the future. There are very few fundamental limitations to what AI technology can do. Therefore, it is important for humans to shift to more strategic and high-stake decision-making roles and for organizations to anticipate and support this shift to achieve both business and human success in the workplace. (Wu)

There’s a simple, complicated, and complex framework that can be applied to determine what tasks can and should be automated versus augmented. Simple is a recipe – a clear set of steps and directions. Complicated is parking a car. Complex is raising a child. AI can help handle and automate most Simple things and many Complicated things. Complex is the domain of humans. For any transformation, you need to address People, Processes and Tools. AI is the tool. People need to develop skills such as improvisation, listening, collaboration, creativity, empathy, situational awareness, sense-making, and critical thinking to use this new set of technologies effectively. Regarding processes, one consideration is how humans can work with AI using these skills, but another important consideration is handling exceptions and then normalizing exceptions so they can be automated in the future. Organizations need to think empower employees to handle exceptions, which they are more likely to face since automation is handling problems with known solutions. To successfully transform processes using AI, organizations need to focus on employee empowerment, collaboration, knowledge management and new metrics. (Berkson)

From the Replacement to the Empowerment of Employees

Empowering employees through AI-assisted tasks and workflows involves integrating artificial intelligence technologies into daily operations to enhance efficiency, accuracy, and decision-making capabilities. By automating routine and time-consuming tasks, AI has the potential to free employees to focus on more complex and creative work, thus boosting both productivity and job satisfaction by enabling employees to focus on higher-value, true knowledge work.

For example, knowledge workers spend a significant amount of time searching for and gathering information. Generative AI can significantly reduce this hunting and gathering task. Employees are then able to engage in “true knowledge work” that requires deep cognitive effort, creative thinking, problem-solving skills, and specialized knowledge. With AI removing mundane, draining tasks, employees can engage in more meaningful work. (Debogovich)

Generative AI’s role in communication provides another powerful example for how employees can be empowered with this technology. In today’s workplace, communication has become increasingly essential. According to the 2024 Study of Business Communication by The Harris Poll and Grammarly, approximately 78% of professionals have experienced a rise in work communication over the past year. This increase has led to knowledge workers spending almost 88% of their workweek communicating with their colleagues and clients. (Artis) 

Generative AI can assist in making business communication easier and faster. From notetaking, to prompts, information synthesis and drafting content and communications, generative AI is increasingly being embedded into online meeting platforms and office programs, including Google’s and Microsoft’s Office platforms.(McClure)

AI can also be a valuable tool for data analysis and decision-making. Organizations have access to a vast amount of data. However, making sense of this data and using it to inform decision-making can be daunting. AI-driven data analysis provides sophisticated algorithms and machine learning capabilities that help organizations identify patterns and insights hidden within their data that might have gone unnoticed. This enables smarter decision-making and can improve overall performance. Whether it’s optimizing marketing campaigns or predicting future financial trends, AI-driven data analysis has the potential to change the way that organizations approach decision-making. (Artis)

From Measuring Productivity to “Progressivity” as a Key Metric of Business and Human Success

Productivity has long been used as a key metric of business success. Productivity is traditionally measured quantitatively and by throughput, e.g., how many widgets can be produced in an hour. Traditional productivity metrics do not track the value of how work gets done, just what is done. Balance sheets do not calculate expertise and uniquely human value as assets. Until the accounting of expertise, experience, and relationships/trust happens, any other effort will fail because the financials do not track this value. (Happe)

Many organizations adopting AI technologies frame the addition of AI into work from a task perspective, a production mindset. This does not take the value of people and their knowledge into account. The limitations of traditional productivity metrics in the AI era are that they lack the ability to measure the value of human work and teams’ progress toward the collective ambition of the organization – which is the central focus of the Team Flow model. 

Some of the biggest challenges organizations face today include retention, engagement, and burnout. Adopting the Team Flow model and a shift toward measuring “progressivity” focuses more on moving toward a common goal or “collective ambition” and improving both teamwork and individual skills rather than on merely measuring quantitative output. 

The Team Flow model provides the opportunity for organizations to shift focus from just what work is done to how teams work together to achieve the collective ambition of the organization. It provides a framework that enables organizations to achieve sustainable progress toward this collective ambition, thereby enhancing the employee experience, meaning, engagement, and dedication for employees working increasingly in a technology-driven, decentralized, asynchronous environment.

Team Flow Institute recommends rethinking metrics and key performance indicators (KPIs) by:

• Defining the objectives that AI can enhance, ensuring alignment with broader organizational goals and strategies
• Identifying and prioritizing AI opportunities based on workload, investment, savings potential and effort
• Focusing on progressivity rather than productivity to measure business and human success. 

(Heuer) (Schwarz)

From Conducting “Business-as-usual” to Envisioning “Business as Possible”

AI has the potential to unlock new opportunities and business models. What was once thought impossible could become possible with the addition of AI. AI technologies are so powerful that they can serve as a toolset and a strategic partner, aiding in data analysis, insight discovery, and decision-making. While this presents potential risks and challenges and underscores the importance of the ethical introduction of AI and good governance, the upside potential is incredible. AI can not only significantly improve, accelerate, and enhance business operations but can also be used to help guide innovation and enterprise strategy, thereby creating a competitive advantage.

In addition to transforming businesses in terms of strategy and operations, AI can transform the organization and employee experience, making work more meaningful and fulfilling for employees if organizations take a human-centric approach to AI integration, supported by strategy, governance, training, and enablement.

The Team Flow Institute Fellows recommend starting with these two questions to begin envisioning new opportunities and the transformative possibilities of integrating AI technology rather than just adopting AI as another new technology and conducting business as usual:

1. What opportunities and challenges do we face in implementing this new technology and what previously impossible tasks can we now tackle with the help of AI?
2. What tasks are we currently performing that AI could automate and what should be augmented through AI to enable our employees to focus on being true knowledge workers?
   
    

This rethinking and reframing of AI’s role in organizations shifts the focus from AI as a tool that could potentially replace human jobs to one that enhances human capabilities and creativity. Integrating AI in workplaces should empower employees, make their jobs more meaningful, and enable them to achieve more than what’s possible manually. This lays the groundwork for a more nuanced approach to how AI can be used as a partner to enhance the value of human work rather than as a substitute for human workers.

Laying the Foundation for Success

In addition to balancing the use of AI for augmentation and automation, empowering employees with new skills and the ability to focus on higher-value tasks — rethinking how to measure success. The successful integration of AI technologies into the workplace requires:

• Developing a comprehensive digital strategy and governance framework
• Implementing effective change management and communication strategies
• Building a healthy culture of trust through transparency, education, and employee empowerment
• Investing in ongoing training and skill development
• Encouraging and supporting continuous learning and upskilling to maximize the benefits of AI augmentation
• Addressing ethical considerations to ensure responsible AI deployment
• Assessing and understanding the impacts to organizational structures and team composition

Developing a Comprehensive Digital Strategy & Governance

Historically, many digital transformation initiatives have failed because of the lack of a comprehensive, coordinated strategy, too many siloed efforts, a lack of skills and expertise, and fear of data privacy, security, and regulatory compliance issues. These challenges only increase with the addition of AI technologies.

In addition, transformations fail due to a lack of effective change management and change communications. Too many organizations focus on technology first. But digital transformation is not just about technology deployment. It is about business transformation in an increasingly digital world. That is especially true with AI, which will change how we all work and live. Digital transformation is about culture,  people, and skill transformation using digital technologies.

The roles and responsibilities for AI strategy and governance need to be defined, including leadership, oversight, and accountability. AI is already being deployed across nearly every business function, from accounting to communications and marketing, customer service and CRM, inventory and supply chain management to recruitment and talent management. The number of functions, along with the vast number of easily available AI tools can lead to siloed efforts, rogue experiments, duplication of efforts, inefficiencies, and increased risk.  

The key to success is to conduct a comprehensive organization-wide assessment to determine where and how AI is and can be best used and to align AI strategy and governance within the organization’s overall digital strategy and business objectives. A Digital Center of Excellence provides an excellent framework for this work. A Digital Center of Excellence is not a new organizational structure. It is a cross-functional, collaborative group, responsible for:

• Establishing and overseeing digital strategy, enablement, and governance
• Developing and maintaining successful standards and processes
• Maximizing the digital capabilities of a team/organization
• Identifying, deploying, and managing best-in-class digital technologies and vendors
• Measuring and regular reporting against an agreed-upon set of metrics 
  
  

From a strategy and governance standpoint, some key considerations and actions include:

• Develop a comprehensive strategy with a “business as possible” mindset and clear goals and objectives—and then clearly communicate that strategy to the entire organization so that everyone understands what’s changing, why, and what the collective ambition is. The lack of clear and effective communication of the strategy and plan across the organization is the primary reason that most strategic change initiatives fail.
• Develop a clear and concise set of guidelines that outline responsible AI use, including ethical guidelines, compliance with regulations, and operational protocols,
  taking into consideration what guardrails and governance structure will work best for your organizational structure
• Implement a robust data governance framework and aligned training and enablement program
• Monitor and evaluate AI initiatives on an ongoing basis to ensure they meet ethical standards, performance expectations, and strategic objectives
• Develop a risk assessment and management plan for AI-related challenges and vulnerabilities
• Foster a culture of transparency and open communication regarding AI adoption and its impact
• Collaborate with external stakeholders, such as industry partners and regulatory bodies, to align AI governance practices
• Develop a crisis management plan to address potential AI-related incidents or failures

(McClure)

Change Management, Communications & Culture

As organizations adopt AI and other innovative technologies, successful implementation relies heavily on effective change management, clear communication, and a supportive organizational culture. 

To truly embrace AI, organizations must go beyond a typical communication campaign to align their efforts with a broader change management model. Whether it’s Kotter, Prosci, Lewin or another change management model, each approach emphasizes the importance of defining a clear vision and strategy for AI implementation. Organizations must align their AI objectives with overarching business goals and values, ensuring that the purpose and benefits of adopting new technologies are well-defined and effectively communicated to all stakeholders. 

But vision and goals are not enough. The success of AI adoption hinges on executive sponsors’ commitment, engagement, and support. Leaders must champion the change, secure buy-in from other leaders, and model desired behaviors. In fact, according to Prosci’s research, active and visible executive sponsorship is the top contributor to successful change initiatives. By providing leaders with the necessary resources and support, organizations can create a solid foundation for AI-driven transformation.

In addition to executive sponsorship, the true power of change lies in the hands of the employees experiencing the change. Organizations must foster a culture of open communication and transparency, actively seeking input and feedback from their teams. 

Effective communication is the key to any successful change initiative. Senior leaders need tools to champion change, while management, employees, and the entire organization must understand and embrace the ‘what, when, why, and how’ of a change initiative to fully participate and successfully support the transformation throughout the journey.

All stakeholders – both internal and external, from leaders to employees to partners, customers and clients must understand the impact of the change on them. It’s OK to not have all the answers. The important thing is constant, consistent and honest two-way communications with all stakeholders. 

By addressing concerns head-on, highlighting the benefits of embracing change, and celebrating the successes of early adopters, organizations can build a groundswell of support for AI adoption. Pilot programs that showcase successes achieved by early adopters can help build momentum and encourage wider adoption across the organization.

But change is not a one-size-fits-all proposition. Organizations can build momentum and manage resistance by:

• Breaking down the implementation process into manageable stages
• Ensuring content is customized and relevant for employees
• Prioritizing high-impact, low-risk initiatives
  
  

These steps should help cultivate a supportive organizational culture and build trust among employees. Encouraging experimentation, risk-taking, and learning from failure promotes innovation and adaptability. Fostering collaboration between human and AI team members, as well as cross-functional collaboration and reverse mentoring, can accelerate productive AI adoption. Transparent communication about the goals and benefits of AI, coupled with comprehensive training resources, helps mitigate misinterpretation and misuse of AI tools. 

Ultimately, effective change management, communication, and a supportive culture are essential for organizations seeking to harness the transformative power of AI and innovative technologies. (McIntosh) (Holtz)

Continuous Learning & Skill Development 

As AI transforms the work landscape, uniquely human skills like critical thinking, creativity, and emotional intelligence become increasingly valuable. While AI is undoubtedly powerful, it can’t replicate the unique qualities that make us human. These human strengths will be crucial for navigating the complexities of the future workplace and ensuring that technology serves as a tool for augmentation, not replacement. (Holtz)

That means that continuous learning and skill development of employees is crucial as AI tools become more ingrained in day-to-day operations. The workforce must have the mindset, knowledge, and skills to work alongside AI. This includes understanding AI’s capabilities and its limitations. Equally important is fostering an environment that values human skills such as creativity, empathy, and complex problem-solving—capabilities that AI cannot replicate. As an AI-enabled workplace continues to evolve, certain hard and soft skills and competencies will become increasingly valuable for employees, including:

AI Literacy: As AI becomes more pervasive in the workplace, individuals must develop a basic understanding of AI concepts, technologies, and applications. This includes familiarity with machine learning, natural language processing, prompt engineering, and data analytics. AI literacy will enable individuals to interact with AI systems effectively, interpret their outputs, and make informed decisions based on AI-generated insights.

Emotional Intelligence and Interpersonal Skills: While AI can automate many tasks, it cannot replace the human touch. Emotional intelligence, empathy, and strong interpersonal skills will be crucial for building and maintaining relationships with colleagues, customers, and stakeholders. As AI takes over more routine tasks, the ability to connect with others on a human level will become a key differentiator.

Critical Thinking and Problem-Solving: As AI automates more tasks, individuals must focus on higher order thinking skills. Critical thinking and problem-solving abilities will be essential for analyzing complex situations, identifying patterns and trends, and making sound decisions. These skills will enable individuals to leverage AI-generated insights and apply them to real-world challenges.

Creativity and Innovation: While AI can generate novel ideas and solutions, human creativity will remain a vital asset in the workplace. The ability to think outside the box, develop original concepts, and drive innovation will be highly valued. Individuals who can harness their creative potential and work collaboratively with AI systems will be well-positioned to contribute to their organizations’ success.

Adaptability and Continuous Learning: The rapid pace of technological change will require individuals to be highly adaptable and committed to continuous learning. As new AI tools and applications emerge, individuals must learn and master them quickly. A growth mindset and a willingness to continuously update one’s skills will be essential for staying relevant in an AI-driven workplace.

Data Literacy and Analytics: As AI relies heavily on data, individuals must develop strong data literacy and analytics skills. This includes collecting, interpreting, and leveraging data to inform decision-making. Understanding how to work with data, derive meaningful insights, and communicate those insights effectively will be critical for collaborating with AI systems and driving business value.

Collaboration and Teamwork: Effective collaboration with human and AI team members will be a key competency in the future workplace. Individuals will need to develop strong collaboration and teamwork skills, including the ability to communicate clearly, work across functional boundaries, and leverage the strengths of human and AI colleagues. Fostering a culture of collaboration will be essential for driving innovation and achieving shared goals.

Ethical Reasoning and Decision-Making: As AI raises complex ethical questions, individuals must develop strong ethical reasoning and decision-making skills. These include navigating ethical dilemmas, considering AI’s implications for various stakeholders, and making decisions that align with organizational values and societal norms. Individuals who can think critically about the ethical dimensions of AI will be well-positioned to guide their organizations in responsible AI deployment.

Cultivating these skills and competencies can position individuals for success in an AI-driven workplace. Organizations that prioritize the development of these skills in their workforce will be better equipped to harness AI’s full potential while ensuring that human expertise remains a vital part of the equation. As the future of work continues to evolve, a commitment to lifelong learning and adaptability will be essential for individuals and organizations.

Ethical Considerations

There are many ethical implications related to introducing AI into the workplace. These include: the potential for worker displacement, and the need to re-train / re-skill and create new career paths for workers. In addition, access, bias, misinformation, fairness, data privacy and security, and transparency. 

Addressing these ethical considerations requires open dialogue, diverse perspectives, and applying robust ethical frameworks into the development of a governance structure. This involves establishing clear guidelines for AI use, ongoing training, enablement, communications, regularly auditing AI usage and systems, and ensuring that how and where AI is being used in the workflow are transparent and explainable. Governance guidelines should ensure that AI systems do not make critical decisions autonomously. Human judgment should always be the final decision-maker, particularly when the issue is sensitive and/or high stakes.

To address these and other ethical considerations, it is important to determine who is responsible for overall AI governance and oversight. Regular reporting to the C-suite and the board is essential to good governance throughout this transformation.

Organizational Design, Structures & Team Composition  

As the adoption of AI becomes more ubiquitous and as AI technology continues to be embedded into technology platforms and across all business functions, there will be significant impacts on and changes to hiring practices, team composition, and organizational design. This will be explored in-depth in future papers by the Team Flow Institute Fellows as well as through case studies gathered by the Institute.

Using Team Flow Principles to Support the Successful Implementation of AI in the Workplace

Team flow is defined as a shared experience of flow derived from optimized team dynamics. (van den Hout) Team flow is achieved through the core elements of mutual commitment with aligned personal goals, high skill integration, safety, trust, communication, a holistic focus and sense of unity and joint progress, all leading to a collective ambition.

These elements and the Team Flow model can be applied to organizations preparing for a successful integration of AI.  Team Flow Institute recommends:

• Aligning people, processes, and AI tools for optimal performance.
• Balancing alignment and professional autonomy consulting AI tools?? (if yet possible)
• Establishing a joint action plan with concrete milestones by AI tools.
• Fostering a culture of collaboration and continuous improvement.
• Encouraging open dialogue and feedback throughout the AI implementation process.
• Promoting transparency and open communication throughout the AI implementation process.
• Merging collective awareness with coordinated action with AI tools.
• Delivering positive and constructive feedback to the team as a performance unit.
• Suggesting personal and team interventions to boost Team Flow through the implementation and integration of these new tools and technologies 

(van den Hout)

Conclusion

The Team Flow Institute Fellows advocate for an approach to AI integration in the workplace that values human work and leverages AI’s potential to augment human capabilities rather than replace them. They advise that organizations prepare for successful AI introduction and integration by adopting the Team Flow model to ensure a healthy culture ready for positive change, innovation, continuous learning, and risk-taking. 

In this paper, the Team Flow Institute’s Fellows have addressed the complexities of AI adoption, the evolving nature of work, and the need for organizations to adapt to technological advancements effectively while addressing these challenges. It highlights the importance of aligning people and processes with the capabilities of AI tools. It stresses the need for effective change management, change communications, constant and open dialogue, and employee empowerment through training and enablement and using Team Flow principles to adapt to these new technological advancements to successfully navigate the evolving landscape of work in the age of AI. Furthermore, this report discusses the ethical considerations surrounding AI development and deployment. The key takeaway is that successful AI implementation requires a strategic approach that aligns with the organization’s broader objectives, incorporates robust strategy, governance, and ethical frameworks, and, most importantly, places humans at the center of technological advancement.

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Editor & Contributors 

Editor:

Jennifer McClure, Senior Fellow & Advisor

Contributors: 

Team Flow Institute Founders: 

Chris Heuer, Co-founder & Managing Director

Jaime Schwarz, Co-founder

Team Flow Institute Senior Fellow & Advisor

Dr. Jef van den Hout, Senior Fellow & Advisor

Team Flow Institute Founding Research Fellows:

Zora Artis, GAICD SCMP CPM leading Alignment, Brand, and Communication Strategist, Advisor, Facilitator, CEO of Artis Advisory and Co-Founder of The Alignment People 

Alan Berkson, Corporate strategist, advisor, and storyteller

Gina Debogovich, Digital leader, innovator, and implementer 

Rachel Happe, Organizational and Business Strategist, Product Executive, Systems Designer, and Community / Culture Change Leader; Founder of Engaged Organizations

Shel Holtz, SCMP, Renowned author, podcaster, corporate communications expert, and Senior Director of Communications for Webcor

Steve King, Partner, Emergent Research, focused on the intersection of the future of work. small businesses and the gig economy

Sharon McIntosh, Certified Professional Coach (CPC), President of And Then Communications & Coaching and Advisor to Executive Communication Council

Dr. Michael Wu, Chief AI Strategist at PROS / Lecturer / Behavior Economist / Neuroscientist

Note: This paper was written with the help of generative AI technology for editing and some content creation. Any AI-generated content has been reviewed, adjusted and enhanced with experience and insights by a human editor to ensure accuracy, relevance and authenticity.