The Adoption Gap: Unlocking the Real Value of AI
“AI delivers value only when organizations prepare, support adoption, and close the gap between potential and practice.”
I’ve noticed that when organizations talk about AI, the focus often goes straight to tools and capabilities. But in my view, the real challenge isn’t the technology—it’s adoption. We can invest in the most advanced systems, yet if people aren’t ready, willing, or supported to use them, the promised value stays out of reach.
Digital transformation has become one of the defining priorities of our time. Organizations across industries are investing heavily in automation and artificial intelligence (AI) to gain agility, efficiency, and competitive advantage. Yet, behind every successful transformation lies an uncomfortable truth: technology alone is never enough. Research consistently shows that more than 80% of digital transformation initiatives fail. And the reason is rarely the technology itself—it’s the people, the culture, and the readiness of the organization to adopt change truly.
This article explores the human challenges of AI adoption as part of digital transformation, drawing insights from a recent SHRM conference experiment and from frameworks that organizations can use to prepare, align, and sustain adoption.
Would You Create Your Digital Clone?
At SHRM, we showed participants a short video about digital clones—AI-enabled versions of ourselves capable of handling up to half of our work. Imagine reclaiming hours for strategy, creativity, or personal priorities because your “digital twin” manages repetitive tasks. After the video, we asked participants: Would you create your own digital clone?
Here’s how people responded:
28 participants: Yes, but only if I could train it very well.
24 participants: I’d use it just for basic tasks.
14 participants: Not now, but maybe in a year.
6 participants: Yes, I need one urgently!
5 participants: Absolutely not.
This pattern reflects what often happens in organizations. When advanced technologies arrive, people don’t usually fall neatly into camps of enthusiasm or rejection. They linger in the middle, in the space of contemplation, weighing trade-offs and imagining consequences. For leaders, this is a critical reminder: adoption is rarely binary—it is a gradual process of guiding people from hesitation to confidence.
Why Adoption Fails
Digital transformation failures are rarely about the tools themselves. They usually stem from gaps in preparation, adaptation, and integration. Our work highlights three invisible but decisive dimensions:
Technical and operational readiness: Are systems, infrastructure, and processes mature enough to support AI? Is there clarity on what the business gains from it?
Psychological and emotional readiness: How do employees feel about the change? Fear of loss, anxiety about competence, or lack of trust can erode even the most promising initiative.
Cultural readiness: Does the collective mindset encourage experimentation, learning, and curiosity? If the culture clings to stability and resists agility, no technology will embed sustainably.
The story of Klarna illustrates this vividly. In 2023, the company replaced 700 customer service employees with AI, only to realize within two years that service quality had declined and trust had eroded. By 2025, they had to rehire people into a hybrid model—proof that even powerful systems fail without alignment between technology, people, and culture.
Ignoring these dimensions can result in costly underuse—or even reversal—of powerful systems. Too many companies purchase advanced platforms capable of extraordinary results, only to discover that employees use a fraction of the features because they never fully adopted the new technology.
Preparing Through Evaluation
The first step is honest preparation. Too often, organizations rush into technology adoption without assessing whether the foundation is strong enough to hold it. A readiness evaluation considers three broad areas: people’s knowledge and skills, the robustness of infrastructure and processes, and the openness of culture and leadership. Frameworks such as MIT’s digital maturity model, Deloitte’s readiness assessments, or Stanford-inspired checklists provide structure to this evaluation.
One practical tool is the BATL model, which asks leaders to evaluate:
Benefits: What advantages will this initiative bring?
Assets: What existing strengths can support it?
Threats: What risks might derail it?
Liabilities: What internal limitations could slow adoption?
This kind of assessment prevents organizations from falling into the trap of adopting technology for its own sake. Had companies like Klarna applied such a structured evaluation before replacing 700 employees with AI, they might have anticipated both the customer backlash and the employee disengagement that eventually forced them into a hybrid model.
Addressing Psychological Readiness
Technology adoption is never just technical—it is deeply personal. People react to change not only with rational analysis but also with emotions. Common psychological barriers include:
loss aversion
the perception that transition costs outweigh benefits
fear of uncertainty
and concerns about losing control.
These are not irrational responses; they are natural human reactions to disruption.
To reduce resistance, leaders need to communicate with clarity and empathy. It helps to highlight tangible benefits, such as the hours of manual reporting saved by automation, and to demonstrate collective gains, like improved collaboration across departments. Comparisons between old and new workflows can prove that the value outweighs the inconvenience of transition. At the same time, peer influence is powerful—employees trust the testimonials of colleagues who are already using a system successfully more than abstract promises from leadership. Training also plays a role, but not in the form of generic sessions. Hands-on workshops where employees practice new skills, receive immediate feedback, and build confidence are far more effective. Finally, visible organizational support, such as assigning contact persons in each department during the early rollout, reassures people that they are not navigating change alone.
These strategies work because they respect the emotional side of adoption. Change is not simply a matter of logic; it is a journey from uncertainty to trust.
Embedding Cultural Readiness
Even with technical preparation and psychological support, culture remains the decisive factor. If an organization’s culture resists experimentation or punishes mistakes, AI initiatives struggle to take root. Cultural readiness is about more than digital literacy; it is about the mindset of curiosity, collaboration, and continuous learning.
Organizations that succeed in adoption often foster what we call digitally literate cultures. In these environments, executives do not expect technology to “work magic” on its own, and employees do not assume that every problem has a simple AI solution. Instead, people approach digital tools with curiosity, a willingness to test and iterate, and respect for the complexity involved.
Frameworks such as ADKAR and Kotter’s 8 steps are particularly useful. ADKAR emphasizes guiding people through awareness, desire, knowledge, ability, and reinforcement, while Kotter focuses on creating urgency, building coalitions, communicating vision, empowering action, and anchoring change in culture. Both remind us that adoption is not an event but a structured process.
Another important element is aligning human resources practices with digital values. Recruitment, evaluation, and recognition systems must reward agility, learning, and collaboration, not only technical performance. Tools such as People Analytics and Organizational Network Analysis provide evidence-based insights. They identify hidden influences and collaboration patterns that either accelerate or block adoption, allowing leaders to mobilize the right people as champions of change.
Finally, communication must be intentional and continuous. A single announcement is never enough. Instead, organizations should use storytelling, visible metrics, and multiple channels to reinforce both the rational case and the emotional meaning of the change.
Turning Resistance Into Dialogue
It is important to recognize that resistance is not always negative. In fact, resistance can be productive. Employees who raise concerns, point out risks, or question assumptions are not necessarily obstructing progress; they may be helping refine it. What leaders must distinguish is between productive resistance, which generates dialogue and improves solutions, and dysfunctional resistance, which blocks progress through disengagement or sabotage.
Creating safe spaces for dialogue allows organizations to capture the value of resistance while addressing its disruptive side. Psychological safety is essential—people must feel that raising questions will not lead to punishment but to better solutions. In this way, resistance becomes an ally in building stronger, more sustainable adoption strategies.
Lessons From SHRM: Adoption as a Journey
Although it may not fully represent the real-life population, the SHRM poll highlighted an important point: when facing new technologies, most people are neither early enthusiasts nor hard resisters—they are in contemplation. For leaders, this means the challenge is not about convincing skeptics or energizing enthusiasts, but about guiding the majority through stages of readiness.
The journey mirrors models of behavioral change: from awareness (“I know AI is coming”), to desire (“I want to try it”), to knowledge (“I know how to use it”), to ability (“I can apply it at work”), and finally reinforcement (“This is how we work now”). Transformation is sustained when leaders design strategies for each stage, instead of assuming that a single communication or training will be enough.
Final Reflection: Adoption Is the Real Transformation
The future of digital transformation does not belong to organizations with the most advanced systems, but to those that can align their people, culture, and operations to adopt them fully. AI has the potential to automate, accelerate, and amplify—but only if humans trust it, use it, and integrate it into how they create value.
The SHRM exercise with digital clones showed us that people are not afraid of AI itself; they are cautious about how it will affect them. Leaders who recognize this hesitation, prepare with care, and embed cultural practices of learning and experimentation will turn adoption into a source of competitive strength.
The essential lesson is simple but profound: AI adoption is not about systems—it is about people. Organizations that thrive will be those that prepare deliberately, support generously, and cultivate cultures where human potential grows alongside technological possibilities.
Make it stand out
Written by Annie-Mariel Arroyo, PH.D
Dr. Annie-Mariel Arroyo-Calixto is a practiced organizational psychologist with more than 28 years of professional experience in organizational change and leadership development. Dr. Arroyo is the founder of Culture To Fit, where for the past 22 years, she has helped leaders build or reshape their organizational culture and lead transformation. She is a seasoned leadership educator and a renowned executive coach known for her ability to guide leaders in gaining deeper insights and self-growth.
