In a recent Reejig webinar, Siobhan Savage (CEO, Reejig) sat down with Itai Asseo (Head of Incubation & Brand Strategy Research at Salesforce) for a future-facing discussion on what it really takes to re-engineer work in the age of AI.
At the heart of their conversation was the concept of Agentic AI, the next evolution beyond predictive and generative systems. But the focus wasn’t just on technology. It was on the operational, cultural, and structural shifts that global enterprises must make to scale AI responsibly and drive measurable impact.
Here are five takeaways from their discussion, offering practical insights for leaders building intelligent systems and preparing their people for the future of work.
According to Itai, 2023 was a year of experimentation: proofs of concept, pilots, and early agent deployments. But in 2024, leading organizations are moving beyond trials and scaling what works across the enterprise.
That shift requires more than deploying tools. It demands clarity around workflows, outcomes, and how people engage with these new systems at scale.
Salesforce’s own platform, Agent Force, is one example of how AI is evolving into something more proactive and embedded. Itai explained that AI has moved from merely generating content to taking context-aware actions within workflows.
He described these agents as always-on, ambient systems, designed to support people in real time, whether in knowledge work or frontline environments.
Both speakers emphasized that real transformation starts with understanding the actual work being done. That means breaking it down at the task level, not relying on legacy job structures or titles.
Itai shared Salesforce’s experience with UCSF Health, where AI was trained using a “learning engine” to capture expert knowledge embedded in day-to-day interactions. Siobhan echoed this with examples from Reejig’s own clients, who are using task-level data to redesign work and unlock capacity.
While technology plays a key role, both Itai and Siobhan emphasized that strong data hygiene and a culture of experimentation and behavior change are the biggest differentiators in successful AI adoption.
Clean, well-organized data ensures AI is learning from the right inputs, while a supportive culture enables teams to explore, test, and iterate safely.
Itai shared how Salesforce leaders model this behavior by using AI tools themselves, signaling to teams that change is not only supported, it’s expected. Siobhan echoed the need for environments where employees feel confident and empowered to experiment, especially when redefining long-standing processes.
Both Itai and Siobhan emphasized that the goal of agentic AI isn’t to displace people—it’s to free them from repetitive tasks and enable deeper focus on creative, strategic, and human-centered work.
They also discussed the importance of evolving workforce models to reflect a blend of human and digital contributors, clarifying roles, skillsets, and task ownership in ways that drive both productivity and employee satisfaction.
This conversation underscored a powerful idea: AI transformation is ultimately about work transformation. Technology may be the enabler, but the real opportunity lies in how we redesign, measure, and experience work itself.
Book a session with a Work Strategist to explore how Work Intelligence can help you rethink work from the ground up.