Guest post by Richard Steele, Execution Specialists Group
In the rapidly evolving landscape of artificial intelligence (AI), the integration of human-centric principles is critical to maximize AI’s full potential while building an AI-ready culture. The success of AI adoption hinges on people and the ways in which they work, far more than on technology alone. But despite a demonstrated potential for AI to turbo-boost productivity and revolutionize work, most organizations struggle to translate AI potential into reality.
Gartner reports that 85% of AI projects fail to deliver expected business value, largely because organizations rush into AI initiatives without adequate planning, workforce training, or change management. About 80% of workers report that their organizations have not provided training on generative AI, leaving a widespread lack of guidance in navigating these advanced tools. The result? Wasted time, frustrated employees, and growing skepticism about AI’s real value.
A 2024 McKinsey study concluded that successful early adopters of generative AI technology focus heavily on educating, upskilling, and reskilling staff to create a new mindset and culture that embraces AI. Here are three human-centered priorities for AI adoption that will improve AI project success and build a workforce that is better prepared for the transformative changes that are coming.
1. AI Literacy as the First Step to AI Success
Leading companies are embracing AI literacy programs designed to equip employees with both technological knowledge and practical application skills. Instead of treating AI as a tool for a select few experts, successful organizations are making AI knowledge accessible to employees at all levels.
Widespread AI literacy helps bridge the gap between IT and business staff by enabling good communication, and fosters the kind of employee confidence that reduces fear and resistance. Furthermore, it helps maximize effective AI use: when employees understand AI, they can better identify opportunities to apply it in their work.
2. Upskilling and Reskilling Prepares Workers for Change
The World Economic Forum noted that AI is transforming entire business models, with more than 40% of companies foreseeing major job disruptions as AI automates some tasks. Companies that invest in upskilling and reskilling can take better advantage of new AI capabilities and retain productive talent rather than replace it.
Organizations that only focus on AI literacy without acknowledging the need for more specific training may struggle to see real productivity gains from AI adoption. But companies that develop general AI knowledge while also preparing staff with focused AI training and new skills as workflows and business needs evolve will see more successful AI projects.
3. Organizational Change Management for AI Adoption
Much like any technology effort, the likelihood of AI adoption success depends more on business process change and human behavior change than the technical deployment. Targeted and intentional organizational change management (OCM) is critical to creating the necessary understanding, desire, and action for change.
Effective OCM will connect current AI projects to company strategy that has been communicated as part of overall AI literacy. This connection to the larger strategic direction can create better context and buy-in for incoming changes. Training that is unique to the project capabilities being introduced and that shows how this project relates to specific business goals can improve workforce performance and comfort. Reinforcement helps to prevent AI abandonment while building new habits that contribute to long term AI adoption success.
Other Considerations for Integrating AI
There are several other human-centered activities a company can implement to support AI integration and encourage creating a culture that is resilient during a time of change.
Continuing Education
Quality academic programs can empower company leaders to adopt AI solutions and be champions for change. For example, the University of Denver has career-focused AI programs through its College of Professional Studies that emphasize IT and AI skills for IT professionals, emerging leaders, and established executives. The master’s concentration and certificate program in AI Strategy and Application in IT was built for working professionals and delivers a powerful combination of industry-aligned skills and academic rigor. The combination of hands-on experiential learning and cutting-edge concepts from thought leaders and industry experts provides the core competencies students need to become knowledgeable and influential AI champions in their organizations to drive innovation and change in this era of AI disruption and opportunity.
Continuous Improvement Practices
Effective feedback loops can help reinforce the importance of the human side of AI adoption when feedback results in visible action. By embedding continuous improvement programs into company culture, organizations create a dynamic environment where employees feel valued, new tools are embraced, and the company is adaptive to the changing technology landscape.
Innovation Programs
Employees are more likely to embrace AI if they see it solving real problems. Innovation teams or programs where fresh ideas are welcomed will allow workers to take an active role in defining how AI fits into their work. A culture that is safe for employees to test AI-related ideas and encourages employees to become internal advocates for adoption can be more effective than top-down mandates.
Call to Action – What can Leaders and Employees Do Now
To bridge the growing gap between AI adoption and workforce readiness, organizations must take a proactive and structured approach that emphasizes the human side of AI adoption. Leaders must be intentional about fostering a culture of AI proficiency that empowers employees to use these technologies effectively. By making AI education and reinforcement a shared responsibility, businesses can foster a workforce that is not only AI-literate but also better prepared for the evolving technological landscape.