Part 2 - Using AI to Transform Marketing

In Part 1, we examined bringing AI-driven products to market and what skills marketing leaders needed to manage buyer psychology, category creation, and speed in this wave of innovation.

In Part 2, we’ll look at internal execution and delivery. Many organizations now prioritize hiring AI-forward marketers, but what does this mean for managing a go-to-market organization? With only three years gone since the ChatGPT moment of November 2022, direct experience is growing but still limited. As with marketing AI products, we’ll need to look at requirements based on analogous experiences and transferable underlying skills, as well as direct execution.

AI transformation is reshaping marketing execution along two critical dimensions:

• Channel effectiveness and management - How AI is disrupting traditional marketing channels and creating new opportunities?
• Workflow and skill evolution - How are AI tools changing day-to-day marketing processes and required competencies?

Marketers have been here before

Marketers have lived through multiple technology transformations over the last 10+ years that have direct analogies to the challenges of deploying AI. It’s worth considering some of these shifts in seeking marketers with applicable experiences:

• Performance/programmatic marketing introduced new campaign technologies, quantitative funnel approaches, and attribution models, which in turn required different creative workflows and analytical skills.
• SEO emerged from black-hat tinkering into a structured discipline, showing how an experimental practice can mature into major traffic channels.
• Data science’s emergence required marketers to partner with engineering and other specialists on data warehousing, predictive modeling, cross-functional data integration, and resulting central/distributed org design questions. 
• MarTech Stacks grew increasingly complex alongside growing campaign sophistication—B2B gained RevOps and ABM platforms while B2C adopted CDPs and multi-touch attribution tools, fundamentally changing how marketers orchestrate customer journeys.

Each transformation included common patterns and skills for marketing leaders that apply to AI transformation:

• Technical fluency became table stakes - Leaders needed enough depth to evaluate vendors, guide strategy, and credibly lead technical teams.
• Cross-functional partnerships expanded, requiring collaboration with engineering, data science, finance, and sales to achieve success.
• The specialist-to-internal journey - Early adopters leveraged agencies and consultants on the bleeding edge, then made strategic decisions about when skills to bring in-house.
• Vendor sprawl followed by consolidation - Each wave brought hundreds of new tools, requiring disciplined testing frameworks before a shakeout over the next 3-5 years. (which will be intense in this case, given the explosion of AI SaaS tools.)
• Success metrics evolved - From impressions to attribution, from leads to pipeline velocity—each wave demanded new measurement frameworks.

It makes sense to seek marketers who led companies through the above group of channel and technology transformations. The second list of skills serves as a guide to probing specific skill sets and approaches used in navigating those changes. 

But What if Everything Changes at Once?

Many marketers have navigated previous technology shifts, but AI is especially challenging because LLMs have suddenly automated knowledge work activities that had resisted prior automation. 

Writing, research, synthesis, brainstorming, video, and image generation went from mostly manual processes to being addressable by software at massive scale overnight. Hence, the earthquake in multiple knowledge work fields, including education, writing, law, and creative arts. This has impacted marketing's entire toolkit—workflows, assets, and channels—while simultaneously roiling the MarTech landscape described in Part 1.

Several specific channels and activities have been especially impacted:

• Creative, production, and approval flows are changed by the ability of anyone on the team to customize and generate visual content at scale.
• SEO and organic traffic are under threat from fundamental shifts in search behavior, from ChatGPT and LLMs becoming a first stop for discovery, and Google’s own aggressive push into AI Mode. Marketers must adapt to new practices of AEO/LLM optimization while confronting net reductions in traffic from the new channels.
• Content marketing and social channels face an arms race of volume and personalization, with LLM content at risk of becoming more generic and less engaging. 
• In B2B, outbound email campaigns and SDR motions that were already saturating start to collapse under their own weight of mass personalization and volume.

In parallel, marketing organizations must develop entirely new skill sets around managing and using AI: 

• Prompting, context development, and agent building for individuals within each marketing function
• Partnership with technical model teams on context development, fine-tuning, and evals as organizations become more sophisticated and invest in building/refining AI directly.
• Human-AI workflow orchestration: Designing optimal hand-offs between human creativity and AI execution, determining which tasks to automate versus preserve for human judgment, and managing hybrid creative processes.
• New metrics and KPIs around AI-driven outputs: agent task completion rates, written content QA, brand/voice adherence levels.

I won’t aspire to solve the future of marketing here, but hiring managers should be wary of marketing leaders locked into existing GTM playbooks without signs of adaptation or creativity. It makes sense to find leaders who have navigated one of the earlier cases of jarring change. Or, someone from an industry that underwent a significant shift (media, e-commerce).

From a channel perspective, marketers may need more skills in channels relevant to the motions discussed in Part 1 - brand, industry narrative, community, ecosystem, and partnerships.

In a world of near infinite content, where highly personalized, “B+” creative is at every person’s fingertips, more nuanced skills around voice will become increasingly important. When the friction in producing marketing outputs approaches zero, the scarce resources become taste and judgment. Marketers will need to craft an authentic, compelling story around a company’s offering and use that to ground and shape the massive output now possible. Some updated version of the brand marketer might be back.

A different channel vector involves product skills. As content becomes commoditized and attention is scarce, the bar goes up for delivering value to prospects. This, combined with AI empowering non-developers to build, has driven notions like “software as content,” where marketing teams create lightweight apps and experiences. These may be upper funnel tools that solve a need of their buyer persona, or, as light sampling and entry points into the product or data around it. Marketers with product management experience or those who have previously built light UX or lead magnet tools have a leg up in this world.

Tinkerer + Process Thinker

To execute on the changes described above, marketers in the age of AI need to be curious and hands-on with the technology. Listening to some podcasts and using ChatGPT to plan vacations won’t cut it. Are they building agents? Can they go down a few levels on the use of context, prompting, MCPs, and nuances between models? The non-deterministic nature of AI necessitates hands-on experience even as a leader to find unlocks, understand what’s brittle, and assess where risks lie.

Finally, there’s a need for process thinking and implementation. These new technologies will likely enable fundamental changes in workflows, requiring marketing leaders to help their teams redesign processes and approvals. Consider these three areas, which have seen some of the most significant early impact from AI workflows:

• Creative production process: Instead of submitting a request for assets to the production team and waiting for deliverables, a marketer might generate their own assets with an AI tool. The creative team’s role is to set brand guidelines in the tool and then monitor the workflow with lighter quality and compliance checks along the way.
• Product Marketing Outputs:  Competitive intelligence gathering transforms from quarterly research producing static battlecards to continuous, automated monitoring by AI agents scraping competitor sites and social signals and updating dynamic materials. PMMs shift from periodic research cycles to defining monitoring parameters, interpreting strategic implications of detected patterns, and communicating highlights to sales.

In these cases, AI tooling shifts processes from sequential steps with clear hand-offs between individuals to more parallel, automated workflows requiring different kinds of design and review roles.  Refactoring these processes and shifting how various marketing specialists do their job is not a trivial undertaking and requires its own set of skills.

The example of Lead Management shows how new levels of scale and depth are possible. Lead qualification and response have shifted from being constrained by SDR capacity to AI-powered processing of every incoming lead. AI agents enrich lead data from multiple sources, score prospects based on intent signals and ideal customer profiles, and provide personalized responses. This enables companies to respond to 100% of leads instantly with tailored messaging, while human SDRs focus on relationship-building with the highest-priority prospects. 

Another potential organizational shift involves how specialization vs generalization will play out:

• One school of thought sees specialized departments (creative, analytics, campaign mgmt) become agents and tools in the hands of every marketer who then becomes more like a mini-GM or category manager. A large CPG has the scale to support Category Managers with functional teams, and AI agents may bring a similar model to startup scale. 
• On the other hand, the increasing sophistication of GTM technology in the past has created additional layers of specialization across areas like mobile UX, conversion rate optimization, data science, etc. We may see individuals going deeper into each function with more powerful AI tools as well.

And just as the rules of company revenue growth have changed, expectations around resources and headcount are in flux. The balance between the leverage provided by AI tools and the increased expectations in creative, content, personalization, and prospect engagement is a moving target, so we’ll see many experiments in various sizes and shapes of GTM organizations. 

However this plays out, marketing leaders will find themselves as change managers and process designers. A marketing operating partner at a leading VC shared that they are seeing success with people who come from consulting and business process engineering backgrounds who know the discipline of breaking down, re-thinking, and re-configuring roles and processes. This is typically a big company skill, but smaller organizations implementing AI-driven GTM workflow changes now need these capabilities."

With so much changing at once, adaptability, agility, and resilience will be critical qualities. Fortunately, those are not new ideas for growth companies, and previous ideas around where to find these kinds of leaders still hold:

• Experiences as founders or in a founding team
• Key leadership or ownership roles in marketing at successful companies through multiple stages of their hypergrowth 
• Experience in fast-changing verticals or ones undergoing a major tech-driven change
• Deep expertise deploying in a relevant channel during its period of transformation or innovation (performance marketing, revenue attribution, ABM scaling) 
• Values that support these kinds of shifts:
  
  • Curiosity - intrinsic interest in learning new things
  • Adaptability - willingness to change, 
  • Humility - comfort with not knowing, openness to new ideas from others, identity not tied to expertise or past successes 

Conclusion: So now we need a Unicorn with Taste, who Vibecodes and loves Process Re-design?

Over the last decade, we frequently heard clients and talent leaders consider the divide between marketing leader archetypes as brand marketers or performance marketers. 

In this article, I’ve considered some new angles on possible archetypes. 

• Market Maker: category creation, brand, narrative building, ecosystem development in fast-moving, undefined markets. 
• Product-Market Navigator: Customer obsession, discipline, and grounding in customer need amidst chaos and hype, product partnerships 
• Execution Innovator: Curiosity, hands-on tinkering with new technologies, flexibility in new approaches
• Change manager: redesigns processes and facilitates role and organizational changes, communicating and leading through disruption. 

Not surprisingly, many talent leaders and CMOs over the past year have questioned whether we are piling additional unrealistic requirements on the already stretched CMO/Head of Marketing function. (Spoiler alert: yes, we are)

So, as always, the key is understanding the specific goals, market, and current capabilities of the hiring org, prioritizing the above skills, and then thinking about how to balance, support, or augment the leader. There’s no one answer, but based on everything we’ve discussed, here are some starting thoughts on must-haves, negotiables, and trade-offs across the market facing and operational areas we’ve discussed:

Non-Negotiables

• A curious, fast moving, adaptive mindset is essential. The velocity of change in buyer behavior, competitive dynamics, and AI workflows means marketing leaders cannot rely on established playbooks or wait for best practices to emerge. They must be comfortable experimenting, failing fast, and pivoting strategies.
• Brand, narrative, and category messaging skills in the leader are needed, given that markets, products, and perceptions are still unformed and shiftin,g and almost every category is affected. Leaders need to understand the stories, content, and channels that drive changing markets. The accelerated growth rates we discussed require scaling as well, but functions like demand gen can be a skill on the leader’s team.
• Hands-on engagement with AI tools and workflows is also key at the leadership level. AI is changing too quickly to just read about it or follow the advice of others. Marketers don’t need to be technical experts, but they do need direct experience to understand what's possible, and to guide their teams credibly.

Context-Dependent Priorities

• Specific vertical experience depends heavily on your market and team composition. Deep vertical solutions like legal, healthcare, or financial services may require a marketing leader who knows those spaces. However, if the founding team or other experts can provide product marketing depth, it may be more important that the marketer brings the right functional skill set.
• Experience leading the entire marketing function is highly valuable, as multiple channels and workflows are changing simultaneously. Marketers with breadth across brand, creative, product marketing, and growth will better understand AI disruptions to each and can more effectively redesign integrated GTM strategies. 

Supplementable, but Important

• Process thinking and change management are necessary, but if we’ve gotten lucky enough to capture the above skills, team members or external resources can supplement this capability by handling process mapping, new role definitions, and workflow design. The leader just needs to value, support, and engage with these initiatives.

At RevelOne, we've never believed in hiring by checklist. The best approach remains starting with business goals and recognizing that different skill combinations can meet the moment. In AI’s uncharted territory, success requires building on the right temperament, identifying the 2-3 capabilities most critical for your market position and stage, and then building systematic plans to supplement the rest.

Marketing has always served as the cross-functional catalyst connecting customer needs, product capabilities, and compelling narratives. The AI era intensifies this role, requiring leaders to navigate chaotic external markets while reinventing their internal operations simultaneously. Those who master both challenges—bringing AI products to market and transforming how marketing works—will shape the defining companies of the next decade.

Appendix: Hiring Guide

The lists below summarizes key ideas discussed in our article "Hiring a Marketing Leader in the Age of AI."

It breaks out the four main competencies discussed across Part 1 - Marketing AI Products and this Part 2 - Using AI to Transform Marketing, and for each, suggests industries and experiences where marketers with relevant experiences might be found, and provides sample questions as a starting point for areas to probe in interviews and assessments.

Marketing AI Products: Category Creation

Relevant Experiences

• Former founders who've pivoted or exited early-stage ventures
• Product marketing leaders from 0-to-1 enterprise SaaS Marketing leaders in the open-source space (GitLab, HashiCorp, MongoDB)
• VPs from companies that renamed/redefined categories (Drift→Conversational Marketing, Gainsight→Customer Success)
• Marketing leaders from blockchain/crypto who navigated undefined markets 2017-2021
• Marketing leaders from successful PLG companies defining new categories (Notion, Airtable)
• Marketing leaders with other relevant experiences:
  
  • B2B influencers/thought leaders with proven audience building and narrative development
  • Marketers with journalism and writing backgrounds or stints as consultants or at innovative product strategy firms.

Sample Interview Questions

• How do you determine if you should create a new category versus positioning within an existing one? What are examples of both that you see in the AI product space?
• How do you think category creation for AI driven companies is similar or different to previous technology waves?
• Describe your process for coining new terminology that sticks. 
• How do you validate category messaging with early adopters vs the broader market?
• Tell me about a time you had to evolve category positioning as competitors emerged
• How do you measure success in the first 18 months of category creation?
• Describe how you'd build industry analyst relationships for an undefined category
• What kinds of content have you found to be most effective in new category creation?
• How has your playbook for category definition changed over the last 3 years?

Marketing AI Products:  Buyer Psychology & Velocity

Relevant Experiences

• Marketing leaders from cybersecurity companies dealing with “Fear Uncertainty Doubt / FUD” type cycles (CrowdStrike, Okta, Zscaler)
• Growth marketers from fintech dealing with trust/regulation (Stripe, Square, Plaid)
• Marketing leaders from viral B2B products (Slack, Zoom, Loom, Calendly)
• Marketing leaders who've worked through platform shifts (mobile-first 2008-2012, cloud migration 2012-2016)
• Growth leaders from successful marketplace/network effects businesses (Uber, DoorDash, Airbnb)
• Marketing leaders from companies that survived competitive blitzes (e.g., Uber vs Lyft wars)
• Wild card: marketers with experience with rapid response PR or crisis management agencies (assuming other relevant experience)

Sample Interview Questions

• Describe your approach to messaging when too many vendor options paralyze buyers
• How do you build trust and reduce perceived risk for buyers when ROI on AI tools is still ambiguous?
• How do you structure messaging differently for individual adopters (bottom-up) vs. executive buyers (top-down) in AI markets?
• Describe what tactics you have used for identifying and riding market momentum waves
• How have you partnered with sales on pilots and other onboard tactics to sell to cautious enterprise buyers? 
• How do you maintain message discipline when shipping features weekly and responding to competitors?
• Tell me about a time you had to completely change GTM strategy mid-flight
• How do you balance brand building with performance marketing at hypergrowth?

Using AI to Transform Marketing: Channel Disruption

Relevant Experiences

• SEO leaders from companies hit by Google algorithm changes (media sites, affiliate, e-commerce)
• Marketing leaders from companies that navigated iOS14/privacy changes
• Marketing/Content leaders from publishers adapting to AI (Buzzfeed, Vice, Vox)
• Marketers with track records launching and scaling multiple new channels
• Former agency executives who've managed digital transformation projects
• Growth PMs who've built marketing-adjacent products and “software as content” (calculators, interactive tools,  assessments) 
• Community leaders who've built engaged audiences without paid acquisition

Sample Interview Questions

• What is your framework for selecting, testing, and scaling new channels? 
• What new channel that you developed surprised you the most and why?
• How would you handle losing 50% of organic traffic in 90 days?
• Describe your approach to marketing when cold email and SDR motions stop working
• Walk through how you'd build a content strategy, assuming AI-generated content is everywhere
• What does ‘taste’ mean to you in marketing content, and how do you measure or cultivate it in a team? 
• Describe your approach to building software products as marketing tools
• How do you maintain brand voice when using AI for content generation?

Using AI to Transform Marketing: Operational Excellence & Change Management

Relevant Experiences

• Former management consultants who moved into marketing and startups
• Marketing Leaders with Ops/RevOps experience in high-velocity SaaS with complex tech stacks or B2C companies with advanced revenue attribution and measurement
• Former founders of marketing automation/martech companies
• Marketing leaders who've managed through M&A integrations
• Marketing leaders from developer tools companies requiring technical depth
• Marketing leaders with experience deploying and upskilling around AI competencies - prompting, agent building

Sample Interview Questions

• Tell me about a time you had to rebuild a marketing function completely. How did you approach changing roles and workflows?
• What AI agents or workflows have you built yourself? (can include personal projects)
• When introducing AI tools to your team, how do you decide what to centralize with specialists versus roll out across the team?
• How do you think about where LLMs work best in automation workflows?
• Describe your approach to change management when team members fear AI replacement
• How do you structure OKRs when capabilities and tools are changing monthly?
• What functions and workflows have you seen most impacted by AI tools, and how did you manage the change?
• How do you think about KPIs for defining AI‑ops maturity (e.g., agent task‑completion, hallucination rate, brand‑voice adherence,) and how do you use them?

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About RevelOne

RevelOne is a specialized go-to-market search & advisory partner that drives Growth through People. Growth strategy and talent strategy are completely intertwined, yet often handled by different people. We staff projects with expertise across both to support our clients in sharpening their growth plans and ensuring they have the right full-time and part-time talent to achieve their specific goals.  

Over the past 10 years, we’ve successfully placed 1,700 people at over 750 clients, including both tech companies and traditional companies looking for modern GTM leaders. Over 50 of these clients are now unicorns.

Our GTM retained search practice focuses on Marketing, Sales, Client Success, and Partnerships/BD permanent hires for all levels, from executives to directors, managers, and team buildouts. We can also source temporary hires – pre-vetted GTM experts – for strategy and execution on interim, part-time, or project-based engagements.

Contact: Have a GTM question, a new hire, or a problem you’d like to solve? Reach out to RevelOne today to discuss: dweiner@revel-one.com