In a recent Reejig webinar, Siobhan Savage (CEO, Reejig) sat down with Itai Asseo (Head of Incubation and Brand Strategy Research at Salesforce). They discussed what it really takes to re-engineer work in the AI era.
At the heart of their conversation was Agentic AI. This is the next evolution beyond predictive and generative systems. The focus was not just on technology. It was on the operational, cultural, and structural shifts that global enterprises must make. They must scale AI responsibly and deliver measurable impact.
Here are five takeaways from their discussion. Practical insights for leaders building intelligent systems and preparing their people for AI-powered work.
According to Itai, 2023 was a year of experimentation. Proofs of concept, pilots, and early agent deployments. In 2024, leading organizations moved beyond trials. They scaled what works across the enterprise.
That shift requires more than deploying technology. It demands clarity around workflows, outcomes, and how people engage with new systems at scale.
Salesforce's own system, Agent Force, is one example. AI is evolving into something more proactive and embedded. Itai explained that AI has moved from generating content to taking context-aware actions within workflows.
He described these agents as always-on, ambient systems. They support people in real time. Whether in knowledge work or frontline environments.
Both speakers emphasized that real transformation starts with understanding actual work. That means breaking it down at the task level. Not relying on legacy job structures or titles.
Every enterprise is deploying AI. Almost none can see the work they're deploying it into.
Itai shared Salesforce's experience with UCSF Health. AI was trained using a "learning engine" to capture expert knowledge embedded in daily interactions. Siobhan echoed this with examples from Reejig's own clients. They use task-level data to redesign work and recover capacity.
Technology plays a key role. But both Itai and Siobhan emphasized that strong data hygiene and a culture of experimentation are the biggest differentiators. These determine successful AI adoption.
Clean, well-organized data ensures AI learns from the right inputs. A supportive culture allows teams to explore, test, and iterate safely. Itai shared how Salesforce leaders model this behavior. They use AI systems themselves. That signals to teams that change is expected. Siobhan echoed the need for environments where employees feel confident to experiment. Especially when redefining long-standing processes.
Both Itai and Siobhan emphasized that the goal of agentic AI is not to displace people. It is to free them from repetitive tasks. It allows deeper focus on creative, strategic, and human-centered work.
They also discussed evolving workforce models. These models reflect a blend of human and digital contributors. They clarify roles, skill sets, and task ownership. This is the Agent + Human Operating Model in practice. It drives both productivity and employee satisfaction.
This conversation underscored a powerful idea. AI transformation is ultimately work transformation. Technology may play a role. The real opportunity sits in how we redesign, measure, and experience work itself.
"We're not just transforming tools. We're transforming how we think about work itself." - Siobhan Savage
The Work Operating System. Critical infrastructure for humans and agents in the AI era.
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