Latest / Uphoff on Media Podcast / What Are Employers Actually Hiring For Right Now?

Transcript

What Are Employers Actually Hiring For Right Now? · Uphoff on Media Podcast

• 0:01
  SPEAKER_00: I'm Tony Uphoff,
• 0:02
  SPEAKER_00: and this is the Uphoff on Media podcast,
• 0:05
  SPEAKER_00: a practical take on how technology is rewriting the way B2B companies get built
• 0:10
  SPEAKER_00: and run and how to get ahead of it.
• 0:12
  SPEAKER_00: For those founding,
• 0:13
  SPEAKER_00: running and funding B2B information,
• 0:15
  SPEAKER_00: marketing and technology companies, the businesses that run business.
• 0:20
  SPEAKER_00: Okay, let's get to work.
• 0:24
  SPEAKER_00: This episode is titled, What are employees actually hiring for right now?
• 0:30
  SPEAKER_00: The attributes employers are hiring for have shifted toward adaptability and AI fluency.
• 0:36
  SPEAKER_00: Most companies are still hiring for what they used to be.
• 0:40
  SPEAKER_00: Agentic AI didn't just change what companies buy.
• 0:44
  SPEAKER_00: It changed who they hire,
• 0:45
  SPEAKER_00: and it changed fast enough that most job descriptions were obsolete
• 0:50
  SPEAKER_00: before HR finished posting them.
• 0:52
  SPEAKER_00: Every senior leader I've talked to this year across ad agencies,
• 0:56
  SPEAKER_00: B2B media and information companies,
• 0:58
  SPEAKER_00: marketing services firms,
• 0:59
  SPEAKER_00: technology CMOs, investors and sales leaders keeps circling back to the same thing.
• 1:06
  SPEAKER_00: The attributes that got someone hired and how to coach
• 1:09
  SPEAKER_00: and manage them are being rewritten in real time.
• 1:13
  SPEAKER_00: Working inside my own advisory clients hiring
• 1:15
  SPEAKER_00: and employee development plans is what made the impact of that shift impossible
• 1:20
  SPEAKER_00: to miss.
• 1:22
  SPEAKER_00: Alex King,
• 1:23
  SPEAKER_00: a recruiter who places talent across SaaS,
• 1:25
  SPEAKER_00: marketing services, and tech startups, already had a name for what I was saying.
• 1:30
  SPEAKER_00: Two hiring waves running at once.
• 1:32
  SPEAKER_00: One builds AI into the product.
• 1:34
  SPEAKER_00: The other,
• 1:35
  SPEAKER_00: almost invisible by comparison,
• 1:37
  SPEAKER_00: builds AI capability into the people already on staff.
• 1:41
  SPEAKER_00: I spent the next few weeks testing that distinction against
• 1:44
  SPEAKER_00: a dozen more conversations,
• 1:46
  SPEAKER_00: a CMO advising Norwest portfolio companies,
• 1:50
  SPEAKER_00: an HR leader who just led her own company through the same transition, a CRO,
• 1:55
  SPEAKER_00: a venture partner,
• 1:56
  SPEAKER_00: and a longtime demand gen operator who sits on several boards in the space.
• 2:00
  SPEAKER_00: Nobody disputed Alex's read.
• 2:02
  SPEAKER_00: Every conversation sharpened it from a different seat,
• 2:05
  SPEAKER_00: marketing, HR, revenue, capital, and the boardroom.
• 2:10
  SPEAKER_00: Companies are hiring for AI in the product.
• 2:13
  SPEAKER_00: Almost nobody is hiring for AI in the workforce.
• 2:17
  SPEAKER_00: Four hiring criteria showed up in nearly every conversation regardless of
• 2:21
  SPEAKER_00: the function stage or operating model.
• 2:24
  SPEAKER_00: Number one, a baseline expectation of demonstrable AI use regardless of the role.
• 2:30
  SPEAKER_00: Number two, little tolerance for a long onboarding or ramp period.
• 2:35
  SPEAKER_00: This is less a preference than a reflection perhaps of how fast the ground is actually moving.
• 2:40
  SPEAKER_00: Number three,
• 2:41
  SPEAKER_00: technical skill in the function,
• 2:43
  SPEAKER_00: usually outranking domain expertise,
• 2:45
  SPEAKER_00: which slid from a requirement to a nice to have.
• 2:49
  SPEAKER_00: And number four, demonstrated skill and mindset prized over years of experience.
• 2:55
  SPEAKER_00: The gap nobody is staffing.
• 2:58
  SPEAKER_00: Every company I talk to has someone building AI into what they sell.
• 3:01
  SPEAKER_00: Almost none of them have someone whose job is making the people already
• 3:05
  SPEAKER_00: on payroll good at using it.
• 3:08
  SPEAKER_00: I named this gap back in the post the AI layoff myth.
• 3:12
  SPEAKER_00: The new roles wouldn't be AI research jobs.
• 3:14
  SPEAKER_00: They'd be built to sit between agentic systems and the human still doing the judgment work.
• 3:20
  SPEAKER_00: Alex put a name on one of them, Enterprise AI Enablement Engineer.
• 3:25
  SPEAKER_00: Sits between business stakeholders and AI systems, builds internal workflows in real time.
• 3:30
  SPEAKER_00: Most companies aren't hiring for it yet.
• 3:33
  SPEAKER_00: The ones that are can't find enough people.
• 3:36
  SPEAKER_00: That gap shows up at the operating layer first in titles like GTM Engineer,
• 3:42
  SPEAKER_00: Director of Revenue Intelligence,
• 3:44
  SPEAKER_00: and Revenue Analytics,
• 3:45
  SPEAKER_00: rules built to optimize AI across go-to-market, not just deploy it.
• 3:52
  SPEAKER_00: A CMO I spoke with called it the biggest shift he's seeing right now,
• 3:56
  SPEAKER_00: concentrated almost entirely inside marketing and revenue operations.
• 4:01
  SPEAKER_00: Then it shows up a level up.
• 4:03
  SPEAKER_00: The same pressure producing GTM engineers below
• 4:06
  SPEAKER_00: the C-suite is producing chief growth officer and chief commercial officer roles
• 4:11
  SPEAKER_00: above it.
• 4:13
  SPEAKER_00: Marketing's standalone impact is declining,
• 4:16
  SPEAKER_00: and the gap between marketing and sales has gotten too costly to manage
• 4:20
  SPEAKER_00: as two functions reporting to two different people,
• 4:23
  SPEAKER_00: same root cause playing out at a different point in the hierarchy.
• 4:28
  SPEAKER_00: A little
• 4:31
  SPEAKER_00: title relabeling, what a strong CRO already does or a real structural shift?
• 4:36
  SPEAKER_00: When I put that question to a CRO I spoke with,
• 4:39
  SPEAKER_00: he waved it off almost entirely and the dismissal turned out to be its own answer.
• 4:44
  SPEAKER_00: He's not thinking about titles or org charts.
• 4:46
  SPEAKER_00: He's thinking about workflows one at a time.
• 4:49
  SPEAKER_00: The pattern underneath both,
• 4:51
  SPEAKER_00: prompt engineering was a role built around a skill, writing good input for a model.
• 4:55
  SPEAKER_00: What's showing up in job titles now is a role built around owning a workflow.
• 5:01
  SPEAKER_00: The loop the model sits inside,
• 5:02
  SPEAKER_00: the same shift I described in loop engineering,
• 5:05
  SPEAKER_00: the bridge to workflow transformation.
• 5:08
  SPEAKER_00: The premium moving from working the tool to owning the standard it runs on.
• 5:12
  SPEAKER_00: The org chart is one step behind the work.
• 5:17
  SPEAKER_00: Solving a one workflow at a time.
• 5:19
  SPEAKER_00: Not everyone I spoke to was building a company-wide agentic AI strategy.
• 5:23
  SPEAKER_00: The CRO told me his team took a different tack.
• 5:26
  SPEAKER_00: Instead of a strategy, they take workflow problems one at a time and ask a single question.
• 5:32
  SPEAKER_00: What did Gentic AI do to improve or transform this specific thing?
• 5:36
  SPEAKER_00: The example he gave me,
• 5:37
  SPEAKER_00: the performance decks his customer experience team builds for clients,
• 5:41
  SPEAKER_00: pulling data from display, lead generation, and lead level detail.
• 5:45
  SPEAKER_00: These used to take several days.
• 5:47
  SPEAKER_00: They now take minutes,
• 5:48
  SPEAKER_00: and the team added something it never had time to do before,
• 5:52
  SPEAKER_00: a specific recommendation for each individual lead.
• 5:55
  SPEAKER_00: The result shows up on every call.
• 5:57
  SPEAKER_00: Reps walk in with something actionable to say, not just a status update.
• 6:01
  SPEAKER_00: He credits that shift with the team's best Q2 in three years.
• 6:06
  SPEAKER_00: His hiring bar has moved with it.
• 6:08
  SPEAKER_00: He's looking for sales reps who are,
• 6:10
  SPEAKER_00: in his words,
• 6:11
  SPEAKER_00: entrepreneurial with AI,
• 6:13
  SPEAKER_00: people who can point to what they've already experimented with rather than waiting
• 6:16
  SPEAKER_00: to be shown.
• 6:17
  SPEAKER_00: A recent hire who beat quota in his first 90 days,
• 6:20
  SPEAKER_00: something he said he hadn't seen before, fit that description exactly.
• 6:26
  SPEAKER_00: He's watching for the opposite signal too.
• 6:28
  SPEAKER_00: A few of his reps still ask about AI enablement sessions.
• 6:32
  SPEAKER_00: He told me that's the wrong question.
• 6:34
  SPEAKER_00: It means the rep is waiting to be told rather than engaging with the technology directly.
• 6:38
  SPEAKER_00: Companies need to own the infrastructure for AI enablement.
• 6:42
  SPEAKER_00: The gap above makes that case.
• 6:44
  SPEAKER_00: The individual people worth hiring into that infrastructure are the ones who don't wait for it.
• 6:50
  SPEAKER_00: I also asked whether management layers are compressing inside revenue organizations
• 6:55
  SPEAKER_00: the way they are elsewhere.
• 6:57
  SPEAKER_00: He didn't frame it as a headcount question.
• 6:59
  SPEAKER_00: His team isn't removing layers.
• 7:01
  SPEAKER_00: They're removing manual work inside the roles that already exist and redirecting
• 7:05
  SPEAKER_00: the time toward the parts of the job only a person can do.
• 7:12
  SPEAKER_00: What's actually changing?
• 7:13
  SPEAKER_00: Evaluation criteria are shifting from track record to demonstrated adaptability.
• 7:19
  SPEAKER_00: That's what I was seeing across my own client roster.
• 7:22
  SPEAKER_00: And the HR leader I spoke with confirmed it from the inside,
• 7:25
  SPEAKER_00: then put herself forward as the example.
• 7:28
  SPEAKER_00: Hired without the full slate of HR credentials on the strength of a mindset
• 7:32
  SPEAKER_00: that proved out once she was in the seat.
• 7:35
  SPEAKER_00: She's rewriting job architecture the same way,
• 7:38
  SPEAKER_00: testing for how fast someone learns rather than what they've already done.
• 7:41
  SPEAKER_00: It's a harder interview question to evaluate.
• 7:44
  SPEAKER_00: It's also by her account, how you find the people who turn into your best hires.
• 7:50
  SPEAKER_00: None of this surprised me.
• 7:51
  SPEAKER_00: Based on input from clients and experts in the field,
• 7:54
  SPEAKER_00: I've built two web-based tools for hiring,
• 7:56
  SPEAKER_00: coaching,
• 7:57
  SPEAKER_00: and managing sales and marketing talent,
• 7:59
  SPEAKER_00: the sales talent matrix and the marketing talent matrix.
• 8:03
  SPEAKER_00: Practical AI fluency has been a formal attribute in the sales version for months,
• 8:08
  SPEAKER_00: added at Alex's suggestion after he kept seeing it separate strong candidates
• 8:11
  SPEAKER_00: from weak ones.
• 8:13
  SPEAKER_00: A CMO I work with helped shape the marketing version the same way.
• 8:17
  SPEAKER_00: Neither of us called it a hiring trend at the time.
• 8:19
  SPEAKER_00: It just seemed like the obvious thing to measure.
• 8:22
  SPEAKER_00: It turned out to be both.
• 8:25
  SPEAKER_00: Depth and originality are gaining value, not losing it.
• 8:28
  SPEAKER_00: The same advisor watching the GTM engineer role emerge is also watching
• 8:32
  SPEAKER_00: the content team shrink and refocus.
• 8:35
  SPEAKER_00: Less volume,
• 8:36
  SPEAKER_00: more original research,
• 8:38
  SPEAKER_00: and point of view work built to stand out against a market flooded
• 8:42
  SPEAKER_00: with generic AI output.
• 8:44
  SPEAKER_00: Trust and differentiation are scarce again, and scarce is valuable.
• 8:49
  SPEAKER_00: Management layers are compressing.
• 8:51
  SPEAKER_00: Scope is redistributing, not eliminated.
• 8:53
  SPEAKER_00: The HR leader I spoke with rebuilt her company's management cadence
• 8:56
  SPEAKER_00: from scratch once managers started carrying more people.
• 9:00
  SPEAKER_00: Structured one-on-one templates,
• 9:02
  SPEAKER_00: a realistic meeting rhythm because no manager with 20 direct reports can run
• 9:07
  SPEAKER_00: the old playbook.
• 9:10
  SPEAKER_00: What isn't changing?
• 9:11
  SPEAKER_00: Comp still matters.
• 9:12
  SPEAKER_00: It's just not the only lever.
• 9:14
  SPEAKER_00: And for the candidates worth competing for, it stopped being the deciding one.
• 9:18
  SPEAKER_00: Expertise still matters.
• 9:19
  SPEAKER_00: What's changing is the packaging.
• 9:21
  SPEAKER_00: Raw credentials carry less weight than proof you can apply what you know fast in
• 9:26
  SPEAKER_00: an environment that won't sit still long enough to hand you a training manual.
• 9:30
  SPEAKER_00: Management still exists.
• 9:31
  SPEAKER_00: It's leaner, and the people left in it are doing more strategic, less administrative work.
• 9:36
  SPEAKER_00: But the function hasn't disappeared.
• 9:38
  SPEAKER_00: It's being redesigned around fewer, better conversations.
• 9:44
  SPEAKER_00: The tension nobody's resolving Alex's read,
• 9:47
  SPEAKER_00: the best AI native candidates are choosing speed and autonomy
• 9:50
  SPEAKER_00: over money consistently because they want to work somewhere that moves
• 9:55
  SPEAKER_00: the way they think.
• 9:56
  SPEAKER_00: A quieter, more transactional read sits right next to that one.
• 10:00
  SPEAKER_00: Call it skills maxing,
• 10:02
  SPEAKER_00: people optimizing their current 40 hours for what they can carry into
• 10:06
  SPEAKER_00: the next opportunity faster rather than committing to a mission.
• 10:10
  SPEAKER_00: Professional development interest,
• 10:11
  SPEAKER_00: largely dormant since 2023,
• 10:14
  SPEAKER_00: is back,
• 10:14
  SPEAKER_00: driven in part by people wanting to bank AI experience they can take with them.
• 10:19
  SPEAKER_00: Both readings are probably true of different people in the same market.
• 10:23
  SPEAKER_00: I'm not going to resolve that tension here, and I'd be suspicious of anyone who claims they can.
• 10:29
  SPEAKER_00: What this means over the next 24 months.
• 10:32
  SPEAKER_00: The company staffing both sides of this wave,
• 10:35
  SPEAKER_00: the product-facing AI team and the workforce-facing one,
• 10:39
  SPEAKER_00: will out-execute the ones only staffing the visible half.
• 10:43
  SPEAKER_00: Right now, most companies are only staffing the visible half.
• 10:46
  SPEAKER_00: That's the opportunity, and it's closing faster than most org charts are moving to catch it.
• 10:51
  SPEAKER_00: A venture partner I spoke with who has 35 active investments across marketing
• 10:56
  SPEAKER_00: and technology, she sees the same thing from the capital side.
• 11:00
  SPEAKER_00: What he's underwriting now isn't proficiency with the technology itself,
• 11:03
  SPEAKER_00: it's the ability to apply agentic AI to an existing business to drive scale
• 11:07
  SPEAKER_00: and revenue growth.
• 11:08
  SPEAKER_00: That's a different bar than knowing how to use the tools,
• 11:11
  SPEAKER_00: and it's the one investors are actually funding.
• 11:15
  SPEAKER_00: For CEOs,
• 11:16
  SPEAKER_00: name a single owner for internal AI enablement now,
• 11:19
  SPEAKER_00: even fractional or borrowed from another function.
• 11:22
  SPEAKER_00: The enterprise AI enablement engineer Gap described earlier doesn't close itself,
• 11:27
  SPEAKER_00: and unowned work never gets done by consensus.
• 11:32
  SPEAKER_00: Rewrite job architecture to test for adaptability is a discipline, not a talking point.
• 11:36
  SPEAKER_00: The HR leader in this piece was hired on that basis herself,
• 11:40
  SPEAKER_00: then rebuilt her own company's job descriptions around
• 11:42
  SPEAKER_00: the same standard once she saw it work.
• 11:46
  SPEAKER_00: And before restoring a management layer,
• 11:47
  SPEAKER_00: make someone justify the span of control with a real cadence,
• 11:51
  SPEAKER_00: not a headcount instinct left over from the org chart you had two years ago.
• 11:55
  SPEAKER_00: That instinct is exactly what keeps companies staffing only the visible half of this wave.
• 12:01
  SPEAKER_00: For operators, skip the company-wide AI strategy document.
• 12:05
  SPEAKER_00: The CRO in this piece produces best Q2 in three years by taking one workflow,
• 12:10
  SPEAKER_00: the client performance deck, and asking a single question.
• 12:13
  SPEAKER_00: What can Nogentic AI change about this specific thing?
• 12:17
  SPEAKER_00: Pick one workflow and answer that question before writing a strategy anyone has to sign off on.
• 12:23
  SPEAKER_00: In interviews,
• 12:24
  SPEAKER_00: listen for whether a candidate is already experimenting with AI unprompted
• 12:28
  SPEAKER_00: on their own time versus asking when the enablement training starts.
• 12:32
  SPEAKER_00: That distinction predicted a rep who beat quota in his first 90 days.
• 12:36
  SPEAKER_00: It reads faster than anything on a resume.
• 12:39
  SPEAKER_00: And when you compress a layer, name exactly where the freed time goes.
• 12:43
  SPEAKER_00: Cutting a layer without redirecting the time
• 12:45
  SPEAKER_00: toward judgment work only leaves you thinner, not sharper.
• 12:49
  SPEAKER_00: And for investors, Stop underwriting proficiency with the tools themselves.
• 12:54
  SPEAKER_00: The venture partner in this piece with 35 active investments across marketing
• 12:58
  SPEAKER_00: and technology has moved past that question.
• 13:01
  SPEAKER_00: He's underwriting whether a team can apply agentic AI to an existing business
• 13:05
  SPEAKER_00: to actually grow revenue, a materially different bar.
• 13:09
  SPEAKER_00: In diligence,
• 13:10
  SPEAKER_00: ask whose judgment is actually encoded into a target's AI-driven workflows and
• 13:15
  SPEAKER_00: whether that judgment survives the departure of the one person who built it.
• 13:20
  SPEAKER_00: An undocumented standard held together by one employee is a retention risk wearing
• 13:24
  SPEAKER_00: an AI capability as a costume.
• 13:27
  SPEAKER_00: Read AI-driven cost cuts skeptically.
• 13:30
  SPEAKER_00: A round of layoffs with an AI label attached is not evidence of anything by itself.
• 13:36
  SPEAKER_00: Ask what got rebuilt, not just what got removed.
• 13:40
  SPEAKER_00: Three different vantage points, the same blind spot underneath.
• 13:43
  SPEAKER_00: Everyone has gotten comfortable evaluating AI and what a company builds or sells.
• 13:47
  SPEAKER_00: Almost nobody has built the discipline to evaluate AI in who a company hires
• 13:52
  SPEAKER_00: and how it develops them.
• 13:53
  SPEAKER_00: That gap is where the next 18 months of B2B leadership actually gets decided.
• 14:00
  SPEAKER_00: And my thanks to everybody who shared their insights and feedback.
• 14:04
  SPEAKER_00: Let me name Alex King,
• 14:05
  SPEAKER_00: Scott Vaughn,
• 14:06
  SPEAKER_00: Emily Hayes,
• 14:07
  SPEAKER_00: Scott Anderson,
• 14:08
  SPEAKER_00: Craig Johnson,
• 14:09
  SPEAKER_00: Tom Click,
• 14:10
  SPEAKER_00: Phil Brandon,
• 14:10
  SPEAKER_00: Tonya Reese,
• 14:12
  SPEAKER_00: Sam Thompson,
• 14:13
  SPEAKER_00: and to the Uphoff Advisory clients whose hiring
• 14:15
  SPEAKER_00: and talent conversations sparked this piece in the first place.
• 14:21
  SPEAKER_00: Well, that's it for this episode.
• 14:25
  SPEAKER_00: If you found this useful,
• 14:27
  SPEAKER_00: Please do one thing, follow the show on Apple or Spotify and leave a rating.
• 14:31
  SPEAKER_00: It's the single best way to help another operator find this.
• 14:35
  SPEAKER_00: I'm Tony Uphoff, back at it next week.