Key Takeaways
- Building AI literacy skills for your go-to-market (GTM) teams creates a competitive edge by turning machine intelligence into daily momentum that accelerates execution, reduces ramp time, and sharpens revenue motion.
- Teams that make the most of agentic and generative AI systems embed intel into real workflows, letting strategic plays emerge from data that updates in context, not from guesswork, workarounds, or manual detective work.
- Adopting artificial intelligence technologies to augment GTM execution requires more than tool access. It means embedding AI where actual work happens so sellers, marketers, and ops teams move smarter and faster as one.
Picture your top rep and account exec 10 calls deep into a six-figure deal:
- Everyone on the buying committee has gone completely dark.
- Your sellers are piecing together notes from their last few meetings and manually cross-referencing LinkedIn profiles and intent data bookmarked weeks ago.
- It’s taking them 45 minutes just to figure out who to follow up with.
- Meanwhile, other opportunities on their plate are being ignored.
Meanwhile, their counterparts at a competitor just queried a purpose-built, easy-to-use AI agent for sales that surfaced the VP Finance’s recent content engagement, flagged a budget cycle shift buried in the company’s earnings call, and recommended a custom ROI narrative tailored to their fiscal priorities.
All in 90 seconds.
In fact, they’ve already sent a personalized follow-up, and the deal’s moving quickly.
This isn’t a hypothetical. It’s happening right now—in your market, with your leads.
Most go-to-market organizations aren’t ignoring AI. The ones who’ve yet to fully capitalize on the emerging technology, though, are simply dabbling with prompt-based tools, running ChatGPT queries for email rewrites, and maybe playing around with a custom chatbot here and there.
But while you’re testing out new tools every other week, your primary competition has graduated beyond basic GenAI use to agentic AI for GTM: autonomous (and semi-autonomous) systems that execute workflows, surface deal-critical insights, and adapt based on real-time signals.
The gap isn’t access. It’s fluency.
AI literacy for go-to-market FAQs
Which AI go-to-market platforms are best for GTM teams who are just getting started with artificial intelligence?
Agentic go-to-market platforms like Highspot make it easy for GTM teams to start fast with built-in AI, once connected to core data sources. The solution’s intuitive UI and easy learning curve reduce the need for sales, marketing, and enablement to rely on technical teams to get going and helps distributed groups apply insights generated by Highspot without the need for heavy, custom configuration.
How can revenue leaders ensure AI literacy is a core part of onboarding and enablement for modern GTM teams?
Sales onboarding should embed the knowledge and skills reps need to navigate and interpret outputs from AI-powered systems across core GTM workflows and decision points. Without structured guidance, teams face risks in understanding what the tools can and cannot do within real workflows, which undermines long-term consistency, adoption, productivity, and value realization.
What steps can GTM leaders take to improve AI literacy among sales, marketing, and customer success teams?
Real-world use cases that reflect current sales motions help go-to-market teams connect AI capabilities to familiar tasks across various touchpoints and KPIs. Instruction must go beyond concepts to show GTM teams how new inputs relate to team priorities and accelerate measurable outcomes across deal execution, campaign planning, competitive response, and post-sale engagement.
How does AI literacy impact long-term success for GTM teams implementing generative AI in their workflows?
High AI literacy ensures consistent agentic and generative AI use while maintaining accuracy, speed, and trust at scale for key motions. Go-to-market teams lacking structured AI tool training often struggle with basic understanding and unknowingly reinforce flawed patterns that limit efficiency, personalization, innovation, and collaboration across critical pipeline and prospecting workflows.
Which training programs best support AI literacy for B2B teams that rely on advanced go-to-market tech stacks?
Top programs focus on developing tactical fluency with artificial intelligence through scenario-based practice, not just general theory or static lectures in isolation. Look for instruction geared toward ‘learners’ working across go-to-market and revenue roles, especially those closest to execution, including sellers, marketers, enablement leaders, and frontline managers who use AI for GTM daily.
How can revenue enablement teams assess the current level of AI literacy across go-to-market business units?
Targeted evaluations using simulations or real platform workflows can reveal ability gaps across go-to-market in how on-the-ground teams perform tasks with AI tools under pressure. Effective audits expose team-level limitations and guide where to focus education efforts next to close GTM performance gaps, reduce friction, drive cross-functional alignment, and improve workflow precision.
What should enterprise RevOps leaders do to build a culture of strong AI literacy across distributed GTM teams?
Revenue operations must set expectations early, create space for experimentation, and integrate AI into go-to-market team feedback loops and success metrics for accountability and clarity. They must reinforce confidence by providing resources that align with how ‘human operators’ in GTM actually work across varied systems, personas, business units, customer lifecycles, and evolving team processes.
Forming an AI literacy framework for your go-to-market organization
Your reps don’t lack the tools. (Well, at least not some AI sales tools—more on that shortly). Rather, they merely lack the capability to wield these solutions as strategic weapons, especially when it comes to AI-powered agents that essentially operate as extensions of your company’s revenue motion.
Every quarter you spend treating AI as an experiment is a quarter you’re hemorrhaging winnable pipeline to orgs that figured this out months ago. They’re faster, sharper, and walking away with deals you should have closed.
Closing that GTM performance gap as it pertains to AI usage and ROI requires more than a Slack channel full of ChatGPT tips or a webinar on prompt engineering. It demands a deliberate, top-down effort to embed AI literacy into the operational DNA of your sales, marketing, and enablement teams.
And it needs to happen before the window slams shut.
The best way for you and other business leaders in go-to-market and revenue to build a community of AI-savvy professionals who can have intelligent conversations with artificial intelligence and drive future GTM success is to:
Standardize agentic and generative AI systems without overwhelming busy personnel
Nothing derails AI rollout for enterprise orgs faster than securing new software that feels like giving GTM teams a second job they didn’t ask for.
Framing both agentic and generative AI technologies as additive instead of disruptive makes onboarding smoother, usage feels intuitive, and small wins stack up without interrupting familiar rhythms or adding unnecessary steps.
Remember: Your people don’t want yet-another system to babysit. Rather, they want a powerful, intuitive tool that quietly handles the lift in the background, then shows up when the stakes are high and decisions really matter.
Action items to establish a strong AI literacy framework:
- Construct a unified sales tech stack that consolidates structured data sources
- Establish baseline workflows that reflect current selling and planning habits
- Automate repetitive motions before introducing more complex AI capabilities
Demystify how AI works in GTM contexts without turning training into homework
Fluency with Ai kicks in when people stop staring at diagrams and start connecting the dots to their actual workflows, customers, and goals. Sales operations must act as de facto ‘teachers’ who translate abstract tools into practical motion, using what reps already know to build skills that stick.
The objective isn’t mastery of how AI models work but just practical understanding of when they’re useful, where they apply, and what to watch for.
If it feels too theoretical, it never makes it past onboarding.
Action items to establish a strong AI literacy framework:
- Assign AI training ownership to enablement leaders with teaching experience
- Translate technical capabilities into real-world business scenarios by role
- Facilitate peer knowledge-sharing sessions anchored in familiar use cases
Systematize knowledge and skills so teams stop guessing and start trusting outputs
Certainty comes from your go-to-market analytics and teaching your GTM staff how to interpret what they’re seeing and where to go from there.
Building the requisite skills and knowledge means helping teams spot signal from noise, then use that clarity to drive better outcomes through making informed decisions tied to high-impact work. This is both data fluency and decision fluency.
Without it, your artificial intelligence outputs become just another passive feed instead of a valuable resource teams use actively and with intention.
Action items to establish a strong AI literacy framework:
- Audit team readiness by testing application, not just recall of AI concepts
- Develop role-based AI fluency goals tied to current team responsibilities
- Publish job-relevant AI checkpoints teams can revisit and iterate on weekly
Normalize effective AI use that feels practical (and not preachy) inside real workflows
Begin with what your go-to-market functions already do, then show where intelligent assistance from AI slots in naturally and without creating friction.
Create moments to celebrate wins and encourage sharing AI-in-sales examples that reflect savvy next steps to better qualify leads, improve deal velocity, adjust objection handling, and keep buyers moving when everything else stalls out.
The fastest way to normalize AI use is to show it saving time inside the work, not outside of it. Once each team sees it makes their job easier and helps them collectively achieve closed-won as one unit, they’ll never want to work without it.
Action items to establish a strong AI literacy framework:
- Encourage teams to document and share efficient AI workflow examples
- Reward process innovation that stems from tactical AI experimentation
- Embed usage prompts into the tools teams already open during core work
Prioritize intuitive AI technologies your staff will actually want to open every day at work
Systems that feel like a timesaver—not a time-suck—are the ones that members of go-to-market org return to without being told or reminded.
Smart bets get made when your sales, enablement, and marketing teams each have the ability to adopt new work approaches freely and apply what works toward buyer engagement efforts that feels human, modern, and relevant.
Nobody wants a dashboard they have to decode. They just want a trusted co-pilot that knows what they’re working on and brings them what matters next without needing to ask. That’s what the best AI sales tools offer today.
Action items to establish a strong AI literacy framework:
- Evaluate new AI solutions by observing non-power users in live work sessions
- Remove unused or duplicative AI systems that reduce team focus and adoption
- Invest in AI-centric platforms with interfaces built around task-first interactions
Empowering your GTM teams to use cutting-edge AI in their day-to-day
If reps are leaving revenue on the table, it’s likely due to poor AI literacy.
“One of the flaws that we’ve seen year after year is that the primary obstacles to effective use of data and AI are almost entirely human rather than technological,” Thomas H. Davenport and Randy Bean, authors of the annual AI & Data Leadership Executive Benchmark Survey, noted in the 2026 edition.
The pair cited a concrete data point proving as much: Around 93% CDOs and CTOs polled pointed to “human issues”—notably, problems around change management—as the biggest AI adoption challenges facing their companies.
Of course, it’s not just SDRs struggling to use the tech efficiently and effectively and embed it in daily workflows. Every GTM team needs to learn how to leverage essential AI tools to show up smarter in deals and close opps faster, together.
Unleashing sales representatives with assistive AI that keeps pace with every deal detail
Reps live inside constant context switching, bouncing from CRM entries to pitch decks to buyer research while the clock keeps ticking. What they crave is embedded intelligence that anticipates what matters next and clears the path forward.
Highspot’s AI revenue enablement platform changes that equation by connecting deal data, content libraries, and buyer insights in one workspace.
Picture this: A seller of yours opening an opportunity instantly sees recommended messaging, competitive positioning, and proven assets mapped to that account profile. Suggested next steps appear in context, not buried in a report.
The experience feels fluid, responsive, and tailored to the deal at hand, allowing SDRs to focus their energy on persuasion, not process management.
Empowering marketing teams to automate relevancy without burning creative cycles
Marketing teams operate at the intersection of creativity and accountability, balancing storytelling with performance pressure. Visibility into how assets influence pipeline often feels distant from day-to-day campaign planning.
Highspot bridges that divide by linking published materials to measurable revenue influence in a single interface. With our agentic GTM platform, your marketers can see which assets are adopted in live deals, which messages resonate in specific industries, and where gaps appear in content coverage.
Planning shifts from assumption-driven brainstorming to insight-driven iteration. Equally as important, creative energy stays intact, while distribution and attribution finally feel connected to tangible business movement.
Equipping sales enablement with intelligent tooling to build skills at the speed of selling
Modern B2B sales enablement leaders carry the weight of preparing teams for complex buyer expectations while keeping ramp times tight. Static training programs struggle to keep pace with evolving market demands.
Highspot embeds adaptive intelligence directly into the seller experience, turning everyday work into continuous skill development. Knowledge checks surface in context, coaching suggestions align with live opportunities, and curated learning paths adjust based on usage data.
Instead of pushing blanket sales training programs, enablement can guide targeted improvement tied to observable performance signals. Development becomes integrated into selling rather than confined to scheduled sessions.
Providing RevOps leaders AI clarity without the pivot tables and overly manual cleanup
Revenue operations teams sit at the intersection of data governance and strategic direction. Inconsistent technology adoption and disconnected tools across their GTM ecosystem often obscure what is influencing pipeline velocity.
Highspot provides a connected intelligence layer that links sales content usage, seller activity, and buyer response into one coherent view.
Leaders can evaluate which assets correlate with opportunity advancement, how teams adopt strategic plays, and where gaps emerge in execution. Planning conversations become grounded in visible evidence rather than anecdotal input.
And strategic adjustments based on data served up by artificial intelligence feel deliberate, informed, and defensible in front of executive leadership.
