Your AI Investment Depends On An AI-Ready Frontline

Companies are spending heavily on AI, and most are not seeing a return.

MIT’s Project NANDA reviewed more than 300 publicly disclosed AI initiatives and found that 95% produced no measurable return, "despite $30-40 billion in enterprise investment."

McKinsey’s 2025 survey on the state of AI paints the same picture from another angle. 64% of companies surveyed say AI is improving innovation, while only 39% report impact on enterprise EBIT.

Cisco’s 2025 survey of 8,000 leaders reported just 13% of organizations are "fully prepared" for AI.

AI is taking on transactional work and freeing frontline teams for higher-value work that is strategic, relational, and dependent on human judgment. Whether associates and frontline leaders are ready for that work determines whether the AI investment earns its return.

AI ROI Comes From Transitioning To Higher-Value Work

Deploying AI is not enough to deliver a return on investment.

McKinsey’s 2025 research shows that the organizations seeing measurable business impact from AI are the ones redesigning their workflows rather than adding AI on top of how they already operate. McKinsey ranks that redesign among the strongest predictors of business impact in its analysis.

The largest returns on an AI investment come when workflow redesign moves people into higher-value work. Automation can take routine tasks off a person’s plate, but the value of the change depends on whether the freed-up time is spent on work that is worth more.

Yet, most organizations have not redesigned their processes. Only 5% of enterprises run AI integrated into their workflows at scale, according to MIT, and 7 of 9 sectors have barely changed how work is organized.

McKinsey calls the companies capturing the most measurable value from AI “high performers,” and what sets them apart is what they are trying to do with the technology. High performers are more than 3x as likely as their peers to be using AI to “bring about transformative change” versus focusing on cutting costs. They are also nearly 3x as likely to have “fundamentally redesigned individual workflows.” The companies that pursue growth and innovation, rather than efficiency alone, post more gains at the enterprise level, including better customer satisfaction, profitability, and revenue growth.

Higher-Value Work Only Pays Off When People Are Ready

The higher-value work people shift into takes human judgment, like deciding whether an AI recommendation is right before acting on it, resolving a case the system could not, or calming a frustrated customer without losing the relationship.

In BCG’s 2025 survey of more than 10,000 employees, only 36% felt the training they had received was enough to use new technology well. Until the people taking on the higher-value work can handle it well, the benefit of AI investments stays out of reach.

The Capabilities For AI Readiness

AI readiness takes 3 things:

• Be open to AI change by building confidence and developing a positive vision for AI-enabled work and career opportunities.
• Become AI-fluent by fostering appropriate trust of AI with an essential understanding of the technology so colleagues can be comfortable and confident working with and alongside AI.
• Build AI-ready capabilities by honing skills increasingly valued as AI absorbs routine work. Examples include complex problem solving, applied judgment, and the ability to navigate high-stakes interactions.

Develop AI Readiness To Match Your Stage On The AI Continuum

How ready a team needs to be rises with each stage of AI adoption, from the lightest use to the most advanced. Here’s how it looks:

• Assistive AI speeds up how colleagues find information. The colleague’s job is to ask the right questions, so they find the right answers within the AI-powered knowledge management tool.
• Integrated AI coaches and checks quality in real time. It rewards colleagues who are coachable and adaptable, as they are the people who are most likely to respond and adjust.
• Predictive AI surfaces signals like fraud or retention risk, enabling proactive action. Acting on those predictive signals calls for strong problem-solving and relationship skills.
• Agentic AI puts colleagues in charge of a set of AI agents. Directing them well requires the ability to manage processes and leverage data to supervise the AI and steer outcomes.

For effective AI adoption, the capabilities must come before, or at minimum alongside, the technology implementation. A team only gets the value of a more advanced stage of AI once the team’s readiness matches its spot on the AI continuum.

Build Readiness Using A Benefit You Already Fund

Frontline associates and leaders want career growth and to feel AI-ready, and leadership needs the frontline to adapt to evolving business needs. Yet, more time for training during the workday is unrealistic for most frontline teams.

Pathstream uniquely unlocks time and motivation after hours for the development that frontline teams want and need. College-credit programs, offered with a national network of university partners, plus practice simulations and coaching tailored to enterprise teams, intrinsically motivate colleagues to invest in themselves.

The AI-ready programs are funded by your company’s existing tuition reimbursement benefit and earn college credit, enabling use outside of work hours. That lets you give your frontline teams the gift of AI readiness with no contracting, no new budget, and no operational disruption.

Pathstream partnered with CMP to add validation by the CMP Certified exam within AI-ready programs for associates and frontline leaders. Go to www.pathstream.com/get-ai-ready to see sample AI-ready college-credit courses and learn more.