AI at Work

What happens when eighty percent of the global workforce receives less than one percent of technology investment, and why has this imbalance gone largely unchallenged for so long?In this episode, I sat down with Emma Seymour, Chief Financial Officer of Deputy, to unpack the realities facing the world’s so-called invisible workforce. Deskless workers power healthcare, retail, hospitality, and frontline services, yet the tools built to support them have historically lagged far behind those designed for office-based teams. Emma brings a grounded, finance-led perspective on why this gap exists and why it is finally starting to close.We explored how AI-driven workforce management is moving beyond hype and into practical, measurable outcomes. From optimizing staffing levels to reduce overstaffing and burnout, to giving workers more control over their schedules through self-service tools, Emma shared how Deputy is translating technology investment into real operational and human impact. We also discussed how AI is reshaping the finance function itself, automating admin-heavy tasks and freeing up teams' time to focus on higher-value work.What also stood out in this conversation was leadership. Deputy’s predominantly female executive team offers a rare example of scaling a billion-dollar technology company while balancing high performance with high care. Emma shared how trust, accountability, and empathy shape decision-making inside the business, and why that culture matters just as much as product innovation when serving a workforce that has been overlooked for decades.As AI continues to accelerate and workforce pressures intensify, what would it look like if more technology companies truly built for the people who keep the global economy running, and how differently might work feel if the invisible workforce finally became visible?Useful LinksConnect with Emma SeymourLearn more about Deputy,Follow on LinkedInThanks to our sponsors, Alcor, for supporting the show.

Are today’s AI tools actually doing the work, or are they still sitting on the sidelines offering advice that humans have to act on?In this episode of the AI at Work podcast, I sat down with Oren Michels, Founder and CEO of Barndoor AI, to explore why so much enterprise AI still feels stuck in what he calls “advisor mode.” We talked about the gap between AI that summarizes and AI that acts, and why that distinction matters far more to knowledge workers than most leaders realize. Oren drew on his experience building Mashery during the early days of APIs, drawing a clear parallel between then and now, when powerful technology exists but remains inaccessible to the people who actually need to use it.We spent a lot of time unpacking what true agentic AI really means inside the enterprise. For Oren, it is not about smarter chatbots or recycled RPA workflows, but about agents that can safely take action inside systems like Salesforce, CRMs, and other tools of record. We discussed why so many AI initiatives fail to deliver ROI, and why the missing skill is often not prompt engineering, but the ability to break real business problems into clear, executable instructions that an AI agent can actually follow.Governance became a central theme in our conversation, especially as we dug into the Model Context Protocol, or MCP. While MCP is emerging as a powerful standard for connecting AI to enterprise tools, Oren explained why it also introduces new security, cost, and control challenges if left unchecked. We explored why governance should act as a launchpad rather than a brake, how least-privilege access changes the conversation, and why the most important question is not how a model was trained, but what it can do with access right now.If you are thinking seriously about agentic AI, enterprise adoption, or how to prevent “bring your own AI” from becoming the next wave of shadow IT, this episode will give you a grounded, experience-led perspective on what actually needs to change inside organizations. As AI agents begin to operate at speed and scale across core systems, are your guardrails designed to stop progress, or to make it possible to move forward with confidence?I would love to hear your thoughts after listening. How close do you think we really are to AI that acts, not just advises?Useful LinksConnect with Oren MichelsLearn more about Barndoor AIThanks to our sponsors, Alcor, for supporting the show.

What does AI at work really look like once the conference buzz fades and teams have to turn ambition into execution?In this episode of the AI at Work Podcast, I sit down with Diego Lomanto, Chief Marketing Officer at Writer, to unpack how marketing teams are actually using AI and agents inside real enterprise workflows. Diego brings a grounded perspective shaped by more than two decades in enterprise software, spanning analytics, automation, and now AI, including his time leading product marketing at UiPath during its rapid growth years.We talk candidly about why AI adoption often stalls inside organizations, not because of the technology, but because leadership behavior, operating models, and incentives fail to evolve. Diego explains why C-level executives need to get hands-on first, why AI should be treated as a transformation of how work gets done rather than another IT rollout, and how marketing leaders need to rethink team structure, workflows, and success metrics in an agent-driven world.The conversation digs into what Diego calls an agentic marketing playbook, where AI handles speed and scale while humans remain firmly in charge of narrative, judgment, and creative direction. From automating repetitive content workflows to freeing up time for deeper customer relationships and high-touch engagement, Diego shares how Writer and its customers, including large consumer brands and regulated enterprises, are using agents to support people rather than sideline them.We also explore how Writer uses its own technology internally, what surprised Diego once AI agents were fully embedded into day-to-day marketing operations, and why change management and AI literacy matter just as much as model quality. As organizations look ahead to 2026, this episode offers a clear-eyed view of where AI-driven work is heading next, from departmental orchestration to deeper collaboration across marketing, sales, and product teams.If AI is quickly becoming table stakes, how will your organization use it to automate the repeatable while keeping humans as the real source of differentiation?Useful LinksConnect with Diego LomantoLearn More About WriterDenodo sponsors Tech Talks Network

As AI moves beyond hype and into everyday operations, many organizations are asking harder questions about impact, trust, and return on investment. Three years on from ChatGPT’s breakout moment, leaders are no longer experimenting for novelty’s sake. They want to know where AI genuinely improves outcomes for employees and customers, and where it risks getting in the way.In this episode of the AI at Work Podcast, I sit down with John Finch, Head of Product Marketing at RingCentral, to unpack how AI is changing customer interactions before, during, and after the call. We explore how tools like AI receptionists and real time agent assistance are helping businesses avoid missed calls, reduce friction, and support frontline teams without turning conversations into scripted or robotic exchanges.John shares RingCentral’s perspective on why voice remains one of the richest and most strategic data sources inside modern organizations. We discuss how insights drawn from real conversations are shaping smarter routing, coaching, and workforce planning, and why sectors like healthcare and financial services are leaning into AI faster than others. At the same time, we address the common mistakes companies make when they bolt AI onto fragmented systems rather than embedding it into a unified platform.Looking ahead to 2026, this conversation also reflects on what AI done well really looks like in the workplace. Not as a replacement for people, but as a way to remove pressure, improve performance, and create better experiences for everyone involved. As AI becomes more natural, conversational, and embedded into daily workflows, the line between digital and human support continues to blur.So as AI becomes part of the fabric of customer operations, how are you balancing automation with empathy, and what lessons from your own organization would you share with others navigating this shift?

What happens when holiday shopping habits shift faster than most small businesses can keep up, and AI becomes the first stop for gift ideas, local searches, and product discovery? In my conversation with Alicia Pringle, Senior Director of Online Marketing at Network Solutions, we look at how the rise of AI-assisted search is changing the game for small business visibility during the busiest season of the year. Alicia brings two decades of marketing experience and a front row seat to the rapid evolution of search, and she breaks down what is really happening behind the scenes as shoppers move from typing into Google to asking Gemini, ChatGPT, and other assistants for personal recommendations.Alicia explains how early holiday behaviour has become and why the traditional mid-December surge is now simply a final sweep rather than the main event. She talks through the surge in AI driven discovery and how more than a third of shoppers now ask AI for curated suggestions with specific personal details baked in. This has created a rare moment where small businesses can compete with large retailers again because AI search rewards clarity, genuine content, and trustworthy online signals rather than the size of a marketing budget. Her examples make it clear that websites, local listings, and social channels now act as one connected reputation system, and AI will only surface businesses that look consistent, human, and helpful across all of them.Throughout our conversation, Alicia brings the ideas to life with practical stories. She shares how a retreat centre in Arizona used smarter positioning, thoughtful content, and simple updates to pull in hundreds of organic clicks right as shoppers were searching for meaningful holiday gifts. She explains how small changes to website speed, photos, clarity, and mobile performance can lift a business in both traditional search and AI powered assistants, often in a matter of hours rather than months. And she makes a strong case for curiosity as the new essential skill, because leaders do not need to understand the mechanics of AI to benefit from it, they simply need to be willing to experiment.As AI search becomes part of everyday life, Alicia’s message is grounding. Visibility can be earned again. Small businesses can adapt. Modern tools can remove a lot of the technical pain. And with a few thoughtful changes, brands can still show up in those key digital moments when customers are ready to buy. So how should small businesses use this moment to build trust, stay discoverable, and meet shoppers where they already are? I would love to hear your thoughts.