Translating AI Potential To Business Value: Takeaways From Our Pilot To Progress Webinar
Artificial intelligence is no longer a distant concept: it's actively reshaping how organizations plan, operate, and deploy talent. Yet, many companies struggle to translate AI’s potential into measurable business value.
Diane Morris from Beamery’s Customer Strategy and Advisory Team and Chris Illingworth, Director, Solution Principal – Skills Intelligence at Beamery, recently shared insights from their work guiding organizations through AI pilots, revealing a practical path to adoption and workforce transformation.
Understanding AI Readiness
Organizations vary widely in how ready they are to adopt AI. Smaller, agile firms and early adopters are often eager to experiment with new technologies, while larger or highly regulated companies may proceed cautiously, navigating governance, compliance, and risk considerations.
Most organizations fall somewhere in between, looking at pilots as a way to learn from early successes before committing fully.
“I think the majority of organizations are falling into some kind of middle bucket, where they want to move forward, but they’re waiting to see what others do that works. And I think where some of these organizations might be struggling is just in understanding how to get started.” – Diane Morris, Beamery
MIT research suggests that 95% of corporate AI initiatives deliver zero returns. Morris highlights the risk of rushing into AI without a clear purpose: leadership mandates and flashy tools alone don’t guarantee meaningful results.
Successful adoption begins with careful, deliberate piloting to understand AI’s potential impact on people, roles, and workflows.
Three Areas Where AI Delivers Impact
Morris highlighted that AI can provide value to HR leaders in three key areas:
- Talent Insights and Workforce Planning: AI tools (like Beamery) can enhance workforce planning by providing predictive insights, helping organizations identify skills gaps, plan talent deployment, and improve workforce strategies.
- Task Automation: Rather than automating entire jobs, AI is most effective at handling discrete tasks, freeing employees from repetitive work and enabling them to focus on strategic, value-added activities.
- Organizational Redesign: As tasks and roles evolve with AI, organizations can proactively redesign workflows, redeploy talent, and upskill employees, ensuring that the human workforce remains central to operational success.
Morris noted that while 30% of work activities could be automated by 2030 (McKinsey), not many jobs have workloads where most tasks (more than half) can be automated. Therefore most roles will require redesign and reskilling, rather than being completely replaced.
“The idea of AI coming in and being a one-to-one replacement for most employees isn’t a reality at this point. AI … however, is certainly going to change the way we work.” – Diane Morris
Best Practices for Piloting AI
Beamery has identified three principles that drive successful AI pilots:
- Pinpoint the problem you need to solve: Clarifying the “why” behind AI adoption ensures alignment across leadership and operational teams. This might be “How do we identify the right talent to accelerate our new product launch?”
- Model the potential workforce impacts: Using a digital organizational twin, companies can simulate things like how AI deployment will affect tasks, skills, and workflows. Leaders can visualize skill gaps, surpluses, and potential redeployment opportunities.
- Transform roles and ways of working: Work on the tactical aspects of the transformation – addressing skills gaps, automating repetitive work, and freeing up human capacity, in line with strategic priorities.
Pilots should be time-bound (typically 4–8 weeks), involving a small group of empowered experts to rapidly generate actionable insights. Iteration is key: organizations don’t need perfect data to start learning.
The Role of the Organizational Digital Twin
A digital organizational twin extends a familiar concept from manufacturing and urban planning into HR.
A digital twin is a detailed virtual replica used to model and predict the impact of change. Shipbuilders use them to test how storms affect ships. Cities use them to simulate road closures. Manufacturers rely on factory twins to spot issues, predict failures, and optimize performance.
Until recently, there was no true equivalent for human capital – no way to model how your workforce might respond to change. Beamery now makes that possible.
An organizational digital twin gives you a living, data-driven view of how your people, skills, roles, and workflows connect and evolve. It’s a virtual map of your organization’s human machinery – continuously updated to reflect how work actually gets done.
Beamery builds this model using:
- Skills intelligence, drawn from HR and business records and enriched with Beamery’s skills ontology and market benchmarks.
- Task intelligence, using AI to break down roles into their component tasks, and also leveraging Beamery’s proprietary data, and external market benchmarks.
Together, these layers ensure that results are contextual, relevant to your company, and up-to-date, and let you simulate different workforce scenarios. You can test how a merger might affect redeployment, explore career pathways, or model the impact of new technology on existing roles and skills.
“When you have this sort of predictive intelligence and an end-to-end view at this level of detail, it really drives much more strategic decision-making – making sure you have the right people, and the right AI tools, in the right places at the right time.” – Diane Morris
Unlocking Value with AI Pilots: From Insight to Action
Implementing AI effectively isn’t just about technology: it’s about people, process, and the right approach. As Chris Illingworth reiterated, successful AI pilots begin with asking the right questions: what problem are we solving, and who benefits from the answers? Involving executive sponsors early ensures the pilot aligns with strategic priorities and demonstrates tangible value across the organization.
Equally important is having the right talent embedded directly in the process. Chris emphasized that Beamery’s forward-deployed teams – where we pair executives with on-the-ground consultants and engineers – are crucial to delivering rapid, actionable results.
Consultants translate data and insights into meaningful business actions, while engineers tackle technical challenges and surface new opportunities. This hands-on approach ensures pilots can run effectively in four- to eight-week cycles, without months spent cleaning or preparing data.
A core focus of these pilots is task-level analysis. Rather than looking only at job titles or broad skill lists, Beamery breaks roles down into the tasks employees perform. By mapping tasks – including frequency, effort, and automation potential – organizations gain context and clarity about how work actually gets done. This allows them to identify opportunities for automation, detect duplicative work, and redeploy talent into higher-value roles.
Chris illustrated the impact of this approach with real outcomes: a pharmaceutical company found that 30% of its tasks were automatable, while a financial services organization discovered significant task duplication across departments. Beamery helped these organizations not just spot opportunities, but implement changes quickly, ensuring employees were placed where their skills could drive the most value.
By combining executive oversight, embedded expertise, and AI-powered task analysis, these pilots enable companies to realize value fast, make informed workforce decisions, and scale improvements across the business.
Conclusion
AI adoption in HR doesn’t have to be daunting. By starting with small, focused pilots, modeling workforce impact with digital twins, and aligning organizational stakeholders, companies can transform insights into action. As Diane Morris said, “Don’t feel like you have to do months and months of prep work just to get started… we don’t want perfect to be the enemy of the good.”
With this approach, organizations can unlock AI’s potential to improve workforce planning, increase productivity, and ensure employees are deployed where they can deliver the most value.