Ricardo Costa plays guitar where almost nobody can hear him. Headphones on, family asleep, he retreats to the basement and makes music for himself. Sometimes the backing band is generated by AI. The chief technology officer of Purolator is quite happy to experiment badly in private. That small detail turns out to be a useful entrance into a much larger question: how do you help thousands of people become comfortable with a technology they are expected to use?
- The offering: Digitate’s interview podcast about enterprise AI and organizational change.
- The audience: technology leaders, strategists, and the teams living through adoption.
- The useful move: listen for a question you can test in your own workplace.
The Intelligent Enterprise begins with this kind of detour. Host Tom Stoneman asks guests what they do when they need some distance from a problem. Coffee, running, ping pong: the activities are ordinary. The stakes in the conversation are less so. These are people deciding how technology enters organizations, how employees learn it, and how much authority a machine should receive.
The guitar player and the training program
In the first interview, released on November 18, 2025, Costa describes an AI training effort built with HR and learning-and-development colleagues. His stated ambition was roughly 1,000 trained employees by year-end. That number was a target. The more interesting detail is the design: people with ambitious ideas could work with specialists, while beginners could start with tools such as Copilot and build an initial agent within a week.
Costa cared about what participants could do afterward. A first agent was a learning exercise. The transferable move is to treat training as organizational work, give people a manageable project, and create a route from curiosity to help. It requires employee time and expert support. A tool subscription alone cannot supply either.
A software company makes room for doubt
The business behind the microphone is Digitate, maker of ignio. Its platform combines observability and AIOps, addressing work such as understanding incidents, resolving operational problems, managing workloads, and monitoring enterprise systems. The podcast occupies the conversation around those purchases: what leaders believe, what teams can absorb, and what has to change before automation becomes useful.
Seen as a publishing strategy, that is a sensible fit. A vendor of autonomous operations has reason to help buyers understand autonomy. The show supplies interviews and an episode archive, with transcripts on Digitate’s website. Its public listening channels include Apple Podcasts, Spotify, and RSS. The distinction matters: a listener gets ideas and examples; a software buyer enters a separate product decision.
Within that commercial setting, the guests leave room for skepticism. Chief data scientist Maitreya Natu discusses the difficulty of trusting AI with business-critical activity. His questions are refreshingly portable: are we solving the right problem, and are we solving it the right way? That places expertise in the choice of problem as well as the algorithm.
“Technology doesn’t drive transformation, people do.”Akhilesh Tripathi, Digitate CEO
Tripathi’s own episode connects ping pong with a mental reset, then distinguishes reacting automatically from anticipating change. The idea gives the show a useful center of gravity. Faster execution can leave the underlying pattern of work untouched. Autonomy demands a clearer understanding of context, and people willing to trust what happens next.
Six weeks to move $10,000
Author Melissa M. Reeve supplies a memorable example of organizational delay. In her interview, she recalls someone at a large enterprise who needed six weeks to obtain approval to shift $10,000 in advertising spend. The ad was underperforming. The person responsible could see it. The permission traveled much more slowly than the information.
To approve moving $10,000 in ad spend, in an example recalled by Melissa M. Reeve. A story about decision friction, not a measured result from the podcast.
Reeve describes AI being added to operating structures that were built for another era. Her factory analogy is straightforward: introducing electricity to a steam-powered operation takes changes to the system around the machinery. Stoneman says her book changed how he thought about his own daily challenges. The conversation moves from buying a capability to redesigning how decisions and work reach one another.
Ritu Dubey approaches the same issue through silos. AI optimized inside sales, finance, or IT can reinforce the boundaries already there. Her argument suggests a failure that arrives before the technology has much chance to prove itself: different departments pursue different outcomes. Making each one faster may simply produce disagreements faster.
Borrow the question, then test it
The format’s difference lies in its attention. Against the familiar enterprise webinar or industry panel, Stoneman keeps returning to one challenge and the person wrestling with it. The off-duty detail makes that person easier to picture. Costa’s private backing band is funny because a senior technologist is using sophisticated machinery for the modest pleasure of playing an imperfect guitar part.
A reader can copy the questioning habit. Pick an episode that matches a current problem. Ask a colleague which assumption deserves testing. For a training project, consider a small cohort, a real task, and someone available to help. For a slow approval process, trace the handoffs before adding another assistant. Those are applications of the conversations, rather than results the show claims to have delivered.
The conditions matter. Interviews compress messy situations into stories. A tactic from a courier company may need substantial changes in a regulated business, a smaller team, or an organization with different data permissions. Listening cannot settle security requirements or establish a return on investment. The sensible cost question concerns the experiment: whose time, which tools, what oversight, and what result would justify continuing?
The people back at their desks
On October 7, 2026, the show widened its angle. Ryan Bascos, Renad Morrar, and Ritu Bhalodia, three early-career Digitate employees in their mid-twenties, joined a conversation about what Gen Z actually thinks about AI. Stoneman and producer Grace Heerman participated too. The episode description asks what growing up alongside a technology does, and does not, teach someone about using it at work.
That is a promising question for this particular publication. Executives can explain the plan. Someone still has to return to a desk and make sense of it. The Intelligent Enterprise earns attention when it helps those two accounts meet. Take a break, hear a person, then return with a better question for the work waiting there.