THIS WEEK'S KEY THEMES
McKinsey’s Tech Trends Report reflects what you all are feeling with AI
OneGTM brings the stats proving GTM Engineering doesn’t mean the same thing to every company.
Its almost Q4 and Hubspot’s latest pricing structure should make you revisit your 2027 budget assumptions.
Addeco launches Agentforce to 40 countries.
Pipedrive moves to general availability.
McKinsey's Tech Trends Report Has the Latest Numbers on AI in the Enterprise Right Now
McKinsey's Technology Trends Outlook 2026 tracks 14 technology trends across innovation, investment, talent demand, and organizational adoption. Two AI-specific trends carry data that RevOps and GTM leaders should have in front of them before Q4 planning locks.
McKinsey finds that 89% of organizations regularly use AI — but only 37% attribute any positive EBIT impact from their AI programs.
That is not a rounding error. It means the majority of organizations running AI are not yet converting usage into measurable financial return. The cost side is moving in the wrong direction simultaneously: 93% of respondents report exceeding their AI budgets. A significant driver of that pressure is compute — a single agentic workflow consumes five to 30 times more tokens than a standard chatbot query. McKinsey now finds that AI accounts for a third of companies' spending to introduce new capabilities, a figure that will move higher as agentic deployments mature.
Only 25% of companies using agentic development tools have achieved meaningful acceleration. In 30% of companies, productivity actually fell after adoption.
The productivity data on agentic software development is equally pointed for any RevOps team building or buying internal tooling. Performance is highly concentrated: the top 20% of engineers see a 55% productivity boost, while the bottom 80% see roughly 3%. McKinsey's read on what separates the two groups: systematic change management and embedding AI into workflows rather than alongside them.
McKinsey's throughline: "Overcoming these roadblocks requires far more than just deploying technology. It requires rewiring operational models from the inside out." This might be a bit dramatic for the commercial org.
Tyler’s Take: Rev, GTM and Sales Ops leaders must resurrect the connector role on your team. This is the person who can define business needs, translate those needs to technical requirements, and hold the rest of the organization accountable to deliver commercial value. Their superpower is facilitating the broader organization on determining “how to” connect the layers that ties models, tools, and workflows into aligned functioning systems.
The State of GTM Engineering 2026 Report by OneGTM Is the First Real Benchmark for the Role — and the Numbers Reflect the Confusion We All Experience About GTM Engineers
OneGTM surveyed 228 practicing GTM Engineers across 32 countries between January and March 2026. It is the first industry-wide benchmark for a role that did not formally exist three years ago and has since posted 5,205% job posting growth. The data is worth reading carefully because it challenges several assumptions practitioners and hiring managers carry about what the role is and how it should be structured.
On compensation: the median GTM Engineer earns $132K. That number covers a wide range — non-coding operators average $110K, while engineers writing Python and building integrations average $155K. The $45K coding premium is the most actionable single finding in the report. Fifty-three percent of respondents are self-taught, the median age is 25, and the role is largely being built from the ground up by practitioners without traditional engineering backgrounds. The equity picture is worse — 68% report no meaningful equity, a significant gap relative to comparable engineering roles that suggests compensation bands are still being set against go-to-market titles rather than technical ones.
On the role itself: the data reveals a bimodal split that most job descriptions ignore.
40% of GTM Engineers code daily or weekly; 45% never code. There is almost no middle ground. These are two distinct sub-roles operating under one job title, which explains the inconsistency in hiring criteria, evaluation frameworks, and output expectations that both hiring managers and candidates describe.
Only 9.6% of respondents expect GTM Engineering to converge with RevOps — which matters for anyone structuring their GTM Ops org and deciding where this function sits.
On bottlenecks: 25% of GTM Engineers cite bandwidth as their primary constraint — not tools, not skills, not executive buy-in. There is simply more work than there are people to do it.
55% of companies do not understand the GTM Engineer role they hired for. They cannot org-chart it, evaluate it, or set appropriate expectations for it.
The result is critical pipeline infrastructure being built without clear organizational support. Tool adoption has effectively saturated — Clay at 84%, CRM at 92%, AI coding tools at 71%. This means the differentiation among GTM Engineers is no longer what tools they use. It is what they build with them, and whether the organization around them knows what to do with the output.
Bonus Tyler Take: The 9.6% who see GTM Engineering converging with RevOps are on the correct side of the prediction if organizations believe in alignment and smooth customer experiences. Why? Because RevOps is chartered to drive alignment of people, processes and tool. If the other 90% are correct, RevOps will become extinct.
HubSpot's Analyst Day Sets the 2030 Target — and Signals a Pricing Model Shift That RevOps Teams Need to Price In Now
HubSpot held its annual Analyst Day this week, with a headline operating margin target of 20–25% by 2030. The number that matters more to RevOps practitioners is the structural change driving it:
HubSpot is transitioning from seats to a hybrid seats-and-credits pricing model.
AI actions and agent interactions will be metered through credits rather than covered by flat seat licenses.
For teams operating under the assumption that their current seat investment covers future AI feature access, that assumption is now formally wrong.
Per-credit costs are still being disclosed on a case-by-case basis in enterprise negotiations, but the direction is clear: the more your team uses Breeze AI, Deal Progression, the revenue agent, and future agentic capabilities, the more variable your HubSpot spend becomes.
Actions for RevOps and Sales Ops leaders: Model credit consumption scenarios now, before contract renewal — not after a mid-year budget variance lands on the finance team's desk.
Adecco's 40-Country Agentforce Rollout Is the First Real Enterprise Test Case for What Was Announced at Dreamforce
Adecco announced a deployment of Agentforce across 40 countries — not a pilot. For RevOps practitioners, it is more useful than any keynote number because it describes what a real enterprise AI deployment actually requires: a defined data model, a governance layer, regional compliance mapping, and a change management program running in parallel across 40 operating environments. Watch Adecco's Q4 and Q1 2027 results reporting — it will be one of the first large-scale Agentforce ROI data points available to the market.
Pipedrive Ships Nova, Its AI Sales Assistant, to General Availability
Pipedrive moved Nova from beta into general availability this week for all Professional and Enterprise customers. Nova surfaces next-best actions, deal summaries, at-risk opportunity flags, and follow-up drafts directly inside the Pipedrive CRM interface with no admin configuration required — on by default from day one.
Pipedrive's positioning is deliberately mid-market: the segment that needs AI-augmented selling capability without the overhead of a full RevOps engineering function. For practitioners evaluating the CRM competitive landscape for mid-market motions, Nova shifts Pipedrive from a roadmap item to a shipping product.
CURATED READS
McKinsey Technology Trends Outlook 2026
McKinsey & Company | September 2026
https://www.mckinsey.com/capabilities/tech-and-ai/our-insights/the-top-trends-in-tech
The 89%/37% EBIT gap, the 93% over-budget finding, the 5–30x token cost multiplier per agentic workflow, and orchestration talent at 0.2x supply-to-demand are the four numbers worth taking into Q4 planning conversations.
State of GTM Engineering 2026
OneGTM | September 2026
https://onegtm.io/research/state-of-gtm-engineering-2026
228 practitioners, 32 countries, the first real benchmark for the role. The bimodal coding split, the 55% company understanding gap, and the 5,205% job posting growth figure are the three findings worth sharing with your leadership team before your next GTM Eng hire.
HubSpot Analyst Day 2026: Seats, Credits, and the Road to 2030
HubSpot Investor Relations | September 2026
https://ir.hubspot.com/events/analyst-day-2026
Margin targets, the seats-and-credits pricing transition timeline, and HubSpot's long-term platform positioning. Required reading before your next contract renewal conversation.
Adecco and Salesforce: A 40-Country Agentforce Rollout in Detail
Salesforce | September 2026
https://www.salesforce.com/news/stories/adecco-agentforce/
The most concrete enterprise Agentforce case study available post-Dreamforce. Read for deployment scope, operational requirements, and what a real rollout — not a proof of concept — actually demands.
Pipedrive Nova Goes GA: What the AI Assistant Actually Does
Pipedrive Blog | September 2026
https://www.pipedrive.com/en/blog/nova-general-availability
Full feature set, availability tiers, and what is and is not included in the GA release versus the upcoming roadmap.
Total estimated read time: under 10 minutes. See you next Friday.
— Parallel OPs
