GenAI Strategy: Who should evangelize and facilitate Generative AI? How about a GenAI SWAT team led by a product marketer?

[Ed – this is a 100% human article; these considerations have not been presented and indexed by LLMs until now!]

This article poses a question that many businesses may be grappling with right now … who should be the key facilitator(s) for exploring and then rolling out GenAI to the organization? Who should be the creator and driver of the tasks that are needed to realize initial and ongoing value. These tasks include research, planning, cross-function collaboration, identification of use cases, selection of public/private/custom GPTs, enablement of users (e.g. prompt training), creation of content usage policies/compliance/standards, and usage analytics. ?This facilitator should also be the opportunist, evangelist and realist for AI business value in the organization.? This role closely coordinates with the C suite (business sponsor) and IT / Data Science (technical enabler).

The short answer to the question is that a current role exists, that is best suited to play GenAI facilitator:? product marketing.? A product marketer is used to defining/explaining product value, identifying business use cases and ROI, enabling/training multiple business functions, creating/managing /analyzing content, and generally being the collaborative glue across the organization.?

• Even better if product marketing has worked with tech products, and fully understands how to generate and message business value from a given technology. ?
• Even better if product marketing proactively researches the avalanche of AI tools, practices and processes, and can identify new candidates for use case consideration.
• Even better if product marketing can evaluate and identify the external use/value of GenAI to extend a company’s product and services (e.g. add a GenAI assistant to help your resellers sell a range of your medical devices)

2023 was perhaps the Wild West of GenAI experimentation, with a huge variation in understanding, usage, experience, and outcomes. ?There was little realization of the downside of this technology, from erroneous results and bad advice, to copyright violations to the leaking of sensitive intelligence into public LLMs.

• BUT, the perceived (and actual) upside can be incredibly compelling, fundamentally changing how people work, making them faster, sharper, more expansive and way more productive.
• The #1 reason why organizations are interested in GenAI is productivity, whether conducting research, generating ideas or creating content. ?This technology is applicable and compelling to every function within the business, whether sales, marketing, finance, HR or customer success.
• SO, individuals have experimented, see the value, and are highly likely to be open to ideas and guidance on how better/best to leverage this technology.
• 2024 is likely to be the year of ‘getting organized’ at the organizational level, and formalizing processes/practices to steadily transform business functions, each with their own specific list of use cases and value propositions.

?

Background: AI at 100,000ft

Everyone has their own background and perception of what AI is and isn’t, so it makes a high-level explanation of Generative AI particularly challenging.

Last week I tried to whiteboard GenAI vs other AI, and the nodding heads inspired me to create a rough PPT slide.

So here is a particularly simplified graphic that tries to explain AI at 100,00ft, with a focus on the primary model types and which ones are best suited to quantitative and qualitative business use cases:

• Supervised and unsupervised machine learning models are mostly regarded as ‘Traditional AI’, and have been around for decades. Many of their business use cases are in the more quantitative areas of prediction, classification and pattern recognition.?? Generative AI models have also been (theoretically) around for decades, but only in the last couple of years have algorithms reached exceptional accuracy to enable mainstream business use, with more qualitative use cases.

GenAI Options at 50,000ft

• There is a spectacular amount of noise and misunderstanding out there regards GenAI platforms, models, tools and practices. ?Big tech and many other new/old vendors are in a gigantic land grab regards market leadership, so beware of marketing hype and FUD.
• There are many options regards what types of GenAI models and GPTS to use, whether open source or proprietary (think public vs private), and whether to build, buy, or blend.
• Microsoft is well positioned to capture GenAI market share regards broad business productivity, as their 365 Office suite natively incorporates their Copilot GPT assistant. ?Google’s Duet AI is also well positioned for those with Google’s suite of applications.
• Customizing GPTs with an intelligently curated set of your documents (a corpus) is essential.? Think of adding your own encyclopedia to the broader knowledge base of the underlying GPT. ?Each business function will have their own encyclopedia, so think carefully about what it contains, as it is a primary data source for generating content and advice for workers. For example, a custom sales GPT needs highly optimized go-to-market content from which to create strategies and tactics for the sales team.
• This topic can get technical in a hurry, so be sure to provide the right amount of information to users of GenAI without scaring them with technobabble!

?

What Next at the Org Level?

• Get organized, but don’t dwell too long before kick-starting your GenAI initiatives and rollout.
• Consider which aspects and angles of your business you would like to enable first, as this drives which domain skills are needed.? Sales and marketing are frequently targeted upfront.
• If you have an evangelist and leader with the skills noted above, consider him/her to be the GenAI facilitator and evangelist.
• Put a GenAI SWAT team together with the right balance of skills, energy and responsibility.? Pick a representative from each business function to be their subject matter expert and facilitator.

• Task the team to create an initial roadmap and framework, with standards, guardrails and use policies. ?Create an impact assessment template for each use case, considering the current/future upside, downside, ethical considerations, and ROI.
• Brainstorm/review use cases with each targeted business function.? Be incredibly collaborative.
• Be sure to create an enablement step (e.g. an interactive workshop) to teach users new skills, such as prompt engineering (or prompt crafting if engineering sounds too technical).
• Be agile, as this technology and space is constantly progressing.? Create a culture where change is the norm, where continual improvement is possible, and expected to maintain competitive advantage.

Be sure to enjoy the journey and smell the flowers.? This is a significant new technology that is utterly transformational, a shiny new object that will quickly become ubiquitous.? Treat it with respect, but grab the opportunity by the horns and maximize what it can do for your business.

?

Thanks very much for your time today!

Feel free to reach out with questions/ideas. Let me know if you need help with (e.g.) assessments of your company’s GenAI opportunity.?

Andy McCartney

#AIinnovation #AIimplementation #generativeAI #machinelearning #artificialintelligence #automation #futureofwork #strategy #digitaltransformation #PMM #ProductMarketing #RunningGenerativeAIProjects #AIProductMarketing #InnovationInMarketing #AIforMarketing #MarketingTechnology #AIProjectManagement