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  • Decoding the C-Suite: Part 5 The Market

    Decoding the C-Suite: Part 5 The Market
    2026/08/18
    This is the final episode of Decoding the C-Suite, a five part miniseries from Recruiting Future about how leadership really thinks about AI, recorded with the leadership team at SmartRecruiters seven months into their acquisition by SAP. Three years into the AI boom, the marketing noise has never been louder. Everything is AI-powered and every vendor makes the same claims. In the final episode, Steve Hardy, who leads marketing at SmartRecruiters, is unusually candid about all of it: why he tells his own sales team to stop demoing, what he calls AI washing, why buyers should start with business priorities rather than features, and what actually builds trust with buyers and candidates alike. The series closes with the question that ran through every conversation: what does good leadership look like in an AI-driven world?
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    27 分
  • Decoding the C-Suite: Part 4 - The Product

    Decoding the C-Suite: Part 4 - The Product
    2026/08/18
    This is episode four of Decoding the C-Suite, a five part miniseries from Recruiting Future about how leadership really thinks about AI, recorded with the leadership team at SmartRecruiters seven months into their acquisition by SAP. AI is moving faster than any buyer can absorb, and that creates a genuine design problem: build for the boldest customers and you lose everyone else, build for the cautious and you fall behind. Shefali Netke, VP of Product Design at SmartRecruiters, lives in that tension every day. She explains how to design for a spectrum of readiness rather than an average user, why she refuses to keep designing for the old world, how her team builds AI fluency, and what it takes to merge two design cultures into one team.
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    25 分
  • Decoding the C-Suite: Part 1 - The Thesis

    Decoding the C-Suite: Part 1 - The Thesis
    2026/08/18
    The organisations genuinely driving AI change in talent all have one thing in common: alignment with the C-suite. Decoding the C-Suite is a five part miniseries from Recruiting Future exploring how leadership really thinks about AI. Recorded over one day with the leadership team at SmartRecruiters, seven months into their acquisition by SAP, the series unpacks AI through five lenses: the thesis, the people, the money, the product and the market. If you want to understand the conversations happening around your own leadership table, and how to win them, this series is for you. In the opening episode, the tables are turned as SmartRecruiters' Allyn Bailey interviews Matt on the future of talent acquisition. Matt shares his honest assessment of the outdated stories the industry keeps telling itself, why mental models matter more than systems, how candidates are already breaking recruiting, and a prediction about AI agents talking to AI agents that he's prepared to be held to. It sets the agenda for the four leadership conversations that follow.
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    25 分
  • Decoding the C-Suite: Part 3 - The Money

    Decoding the C-Suite: Part 3 - The Money
    2026/08/18
    This is episode three of Decoding the C-Suite, a five part miniseries from Recruiting Future about how leadership really thinks about AI, recorded with the leadership team at SmartRecruiters seven months into their acquisition by SAP. If you've ever struggled to get AI investment signed off, this episode is for you. Tom DiDesidero, CFO at SmartRecruiters, explains exactly what he wants to see in a business case, why he backs short, measurable pilots over big commitments, and how to bring evidence rather than instinct. He also lifts the lid on the real economics of AI, from unpredictable inference costs to gross margins far below anything the SaaS world is used to, and makes a prediction about how the AI and SaaS worlds inevitably come together.
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    24 分
  • Decoding the C-Suite: Part 2 - The People

    Decoding the C-Suite: Part 2 - The People
    2026/08/18
    This is episode two of Decoding the C-Suite, a five part miniseries from Recruiting Future about how leadership really thinks about AI, recorded with the leadership team at SmartRecruiters seven months into their acquisition by SAP. The headlines about AI and the workforce are relentlessly grim: surveillance, layoffs, roles disappearing. Lehua Stonebraker, who leads the people function at SmartRecruiters, starts from a different place: naming the fear rather than managing around it. In this episode she explains how to build psychological safety when employees are scared to admit they use AI, why she believes the org chart is gone, how engagement went up during an acquisition, and a vision of a connected employee lifecycle that finally uses everything an organisation learns about its people.
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    23 分
  • Ep 817: The Human Bias Fueling Talent Shortages

    Ep 817: The Human Bias Fueling Talent Shortages
    2026/08/13
    Cybersecurity is one of the hardest markets to hire in, and a lot of the difficulty comes from how companies approach the process. Candidates are still being filtered on degrees, previous employers, and years of experience- signals that are particularly weak in a field where the best work is confidential, and skills need updating constantly. Good people are getting screened out, and what looks like a talent shortage can often be a matching problem. So, what changes when companies stop filtering on the usual proxies and start hiring on what candidates can actually do? My guest this week is Laurent Halimi, CEO and founder of Cyberr.ai, a professional network for cybersecurity professionals. In our conversation, Laurent explains why the skills shortage in cybersecurity is only half the truth, where the bias in hiring really comes from, and what it takes to judge candidates on skills that you can actually verify. In the interview, we discuss: How AI is changing what cybersecurity professionals do and the new roles it is creating A real skill gap at the senior level and a matching problem everywhere else The certification race and why it is losing relevance Why hiring in cybersecurity is different from other technical fields Trust, stale skills, and work that stays invisible Where the bias in hiring algorithms really comes from Practical steps for judging candidates on verifiable skills Anonymous applications and giving candidates control of their profiles Will skills finally beat pedigree, and what does the future look like? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.
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    18 分
  • Ep 816: Hiring For Judgment In The AI Era

    Ep 816: Hiring For Judgment In The AI Era
    2026/08/11
    There is growing consensus that AI is eroding the experience pathways organizations depend on to develop human judgment. Entry-level roles are shrinking, hands-on work is being automated, and fewer people are building the experience their businesses need. This is a well-documented challenge. What remains far less clear is what the talent strategy response should look like. Most skills systems today are built to track whether someone can execute a task, not how well they make decisions under ambiguity. If judgment is becoming the most important capability in the organization, recruiting, learning, and assessment all need recalibrating around it. So what does that recalibration look like in practice? My guest this week is Craig Friedman, author of Enterprise Skills Unlocked and Talent Transformation Leader at St. Charles Consulting Group. In our conversation, he explains why current skills infrastructure misses the capability that matters most, what work looks like when execution is automated, and how organizations can start building judgment into their talent strategy. In the interview, we discuss: What does enterprise AI adoption currently look like The long-term consequences of cutting entry-level jobs What does work look like when the automatable tasks are taken away? Why judgment is more important as a skill than ever before The difference between judgment and critical thinking Where does judgment fit into the skills infrastructure? How can TA teams hire for judgment? What does the future look like? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.
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    23 分
  • Ep 815: Do You Know How Work Gets Done?

    Ep 815: Do You Know How Work Gets Done?
    2026/08/07
    AI adoption is accelerating, but for most organisations it is still ad hoc. Tools are bought reactively, budgets keep growing, and few leaders can say with confidence what is being used, what is working, or what return they are getting. Some companies are already going further, cutting roles on the assumption that machines can simply take over tasks from people. What rarely gets examined is what those decisions do to the people who remain, the culture they work in, and the customers they serve. So what do organisations need to understand about how work happens before they let AI reshape it? My guest this week is Sam Naficy, Chairman and CEO of Prodoscore, a data analytics company that studies employee engagement, productivity, and collaboration in large enterprises. In our conversation, Sam shares what his data reveals about AI use and productivity, the cultural consequences of automating roles, and why visibility into work has to come before automation. In the interview, we discuss: Why most organisations are still in the early stages of AI adoption The growing gap between AI spending and visibility into what is being used What the data shows about heavy AI users and productivity Why some employees adopt AI faster than others The unforeseen impact of automation on workplace culture What happens to the teams that remain when their AI replaces their colleagues Stress-testing workforce changes before making them The line between visibility and surveillance What does the future of work look like?
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    21 分