Tag Archives: Gen AI

What Are We Going to Do Now with GenAI?

What Are We Going to Do Now With GenAI?

GUEST POST from Geoffrey A. Moore

In 2023 we simply could not stop talking about Generative AI. But in 2024 the question for each enterprise became (continuing to today) — and this includes yours as well — is What are we going to do about it? Tough questions call for tough frameworks, so let’s run this one through the Hierarchy of Powers to see if it can shine some light on what might be your company’s best bet.

Category Power

Gen AI can have an impact anywhere in the Category Maturity Life Cycle, but the way it does so differs depending on where your category is, as follows:

  • Early Market. GenAI will almost certainly be a differentiating ingredient that is enabling a disruptive innovation, and you need to be on the bleeding edge. Think ChatGPT.
  • Crossing the chasm. Nailing your target use case is your sole priority, so you would use GenAI if, and only if, it helped you do so, and avoid getting distracted by its other bells and whistles. Think Khan Academy at the school district level.
  • Inside the tornado. Grabbing as much market share as you can is now the game to play, and GenAI-enabled features can help you do so provided they are fully integrated (no “some assembly required”). You cannot afford to slow your adoption down just at the time it needs to be at full speed. Think Microsoft CoPilot.
  • Growth Main Street (category still growing double digits). Market share boundaries are settling in, so the goal now is to grow your patch as fast as you can, solidifying your position and taking as much share as you can from the also-rans. Adding GenAI to the core product can provide a real boost as long as the disruption is minimal. Think Salesforce CRM.
  • Mature Main Street (category stabilized, single-digit growth). You are now marketing primarily to your installed base, secondarily seeking to pick up new logos as they come into play. GenAI can give you a midlife kicker provided you can use it to generate meaningful productivity gains. Think Adobe Photoshop.
  • Late Main Street (category declining, negative growth). The category has never been more profitable, so you are looking to extend its life in as low-cost a way as you can. GenAI can introduce innovative applications that otherwise would never occur to your end users. Think HP home printing.

Company Power

There are two dimensions of company power to consider when analyzing the ROI from a GenAI investment, as follows:

  • Market Share Status. Are you the market share leader, a challenger, or simply a participant? As a challenger, you can use GenAI to disrupt the market pecking order provided you differentiate in a way that is challenging for the leader to copy. On the other hand, as a leader, you can use GenAI to neutralize the innovations coming from challengers provided you can get it to market fast enough to keep the ecosystem in your camp. As a participant, you would add GenAI only if was your single point of differentiation (as a low-share participant, your R&D budget cannot fund more than one).
  • Default Operating Model. Is your core business better served by the complex systems operating model (typical for B2B companies with hundreds to thousands of large enterprises for customers) or the volume operations operating model (typical for B2C companies with hundreds of thousands to millions of consumers)? The complex systems model has sufficient margins to invest professional services across the entire ownership life cycle, from design consulting to installation to expansion. You are going to need deep in-house expertise to win big in this game. By contrast, GenAI deployed via the volume operations model has to work out-of-the-box. Consumers have neither the courage nor the patience to work through any disconnects.

Market Power

Whereas category share leaders benefit most from going broad, market segment leaders win big by going deep. The key tactic is to overdo it on the use cases that mean the most to your target customers, taking your offer beyond anything reasonable for a category leader to copy. GenAI can certainly be a part of this approach, as the two slides below illustrate:

Market Segmentation for Complex Systems

In the complex systems operating model, GenAI should accentuate the differentiation of your whole product, the complete solution to whatever problem you are targeting. That might mean, for example, taking your Large Language Model to a level of specificity that would normally not be warranted. This sets you apart from the incumbent vendor who has nothing like what you offer as well as from other technology vendors who have not embraced your target segment’s specific concerns. Think Crowdstrike’s Charlotte AI for cybersecurity analysis.

Market Segmentation for Volume Operations

In the volume operations operating model, GenAI should accentuate the differentiation of your brand promise by overdelivering on the relevant value discipline. Once again, it is critical not to get distracted by shiny objects—you want to differentiate in one quadrant only, although you can use GenAI in the other three for neutralization purposes. For Performance, think knowledge discovery. For Productivity, think writing letters. For Economy, think tutoring. For Convenience, think gift suggestions.

Offer Power

Everybody wants to “be innovative,” but it is worth stepping back a moment to ask, how do we get a Return on Innovation? Compared to its financial cousin, this kind of ROI is more of a leading indicator and thus of more strategic value. Basically, it comes in three forms:

  1. Differentiation. This creates customer preference, the goal being not just to be different but to create a clear separation from the competition, one that they cannot easily emulate. Think OpenAI.
  2. Neutralization. This closes the gap between you and a competitor who is taking market share away from you, the goal being to get to “good enough, fast enough,” thereby allowing your installed base to stay loyal. Think Google Bard.
  3. Optimization. This reduces the cost while maintaining performance, the goal being to expand the total available market. Think Edge GenAI on PCs and Macs.

For most of us, GenAI will be an added ingredient rather than a core product, which makes the ROI question even more important. The easiest way to waste innovation dollars is to spend them on differentiation that does not go far enough, neutralization that does not go fast enough, or optimization that does not go deep enough. So, the key lesson here is, pick one and only one as your ROI goal, and then go all in to get a positive return.

Execution Power

How best to incorporate GenAI into your existing enterprise depends on which zone of operations you are looking to enhance, as illustrated by the zone management framework below:

Zone Management Framework

If you are unsure exactly what to do, assign the effort to the Incubation Zone and put them on the clock to come up with a good answer as fast as possible. If you can incorporate it directly into your core business’s offerings at relatively low risk, by all means, do so as it is the current hot ticket, and assign it to the Performance Zone. If there is not a good fit, consider using it internally instead to improve your own productivity, assigning it to the Productivity Zone. Finally, although it is awfully early days for this, if you are convinced it is an absolutely essential ingredient in a big bet you feel compelled to make, then assign it to the Transformation Zone and go all in. Again, the overall point is manage your investment in GenAI out of one zone and only one zone, as the success metrics for each zone are incompatible with those of the other three.

One final point. Embracing anything as novel as GenAI has to feel risky. I submit, however, that in 2025 not building upon meaningful GenAI action taken in 2024 is even more so.

That’s what I think. What do you think?

Image Credit: Pexels

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Generation AI Replacing Generation Z

Generation AI Replacing Generation Z

by Braden Kelley

The boundary lines between different named generations are a bit fuzzy but the goal should always be to draw the boundary at an event significant enough to create substantial behavior changes in the new generation worthy of consideration in strategy formation.

I believe we have arrived at such a point and that it is time for GenZ to cede the top of strategy mountain to a new generation I call Generation AI (GenAI).

The dividing line for Generation AI falls around 2014 and the people of GenAI are characterized by being the first group of people to grow up not knowing a world without easy access to generative artificial intelligence (AI) tools that begin to transform their interactions with our institutions and each other.

We have already seen professors and teachers having to police AI-generated school essays, while the rest of us are trying to cope with frighteningly realistic deep fake audio and video. But what other impacts on people’s behavior will we see as a result of the coming ubiquity of artificial intelligence?

It is important to remember that generative artificial intelligence is not really artificial intelligence but collective intelligence informed by what we the people have contributed to the training/reference set. As such these large language models are predicting the next word or combining existing content based on whatever training set they are exposed to. They are not creating original thought.

Generative AI is being built into nearly all of our existing software and cloud tools, and GenAI will grow up only knowing a reality where every application and web site they interact with will have an AI component to it. Generation AI will not know a time where they cannot ask an AI, in the same way that GenZ relies on social search, and Gen X and Millenials assume search engines hold their answers.

Our brains are changing to focus more on processing and less on storage. These changes make us more capable, but more vulnerable too.

This new AI technology represents a double-edge sword and its effects could fall on either edge of the sword in different areas:

Option 1 – Best Case

  • Generative AI will amplify creativity by encouraging recombination of existing images, text, audio and video in new inspiring ways using the outputs of AI as inputs into human creativity

Option 2 – Worst Case

  • Generative AI will reduce creativity because people will become reliant on using artificial intelligence to create, creating an echo chamber of new content only created from existing content, leading to AI outputs becoming the only outputs and a world where people spend more time interacting with AI’s than with other people

Which of these two options on the impact of AI reliance do you see as the most likely in the areas where you focus?

How do you see Generation AI impacting the direction of societies around the world?

Are you planning to add Generation AI to your marketing strategies and strategic planning for 2024 or beyond?

Reference

For reference, here is timeline of previous American generations according to an article from NPR:

Though there is a consensus on the general time period for generations, there is not an agreement on the exact year that each generation begins and ends.

Generation Z – Born 2001-2013 (Age 10-22)

These kids were the first born with the Internet and are suspected to be the most individualistic and technology-dependent generation. Sometimes referred to as the iGeneration.

EDITOR’S NOTE: This description is erroneous, the differentiating factor of GenZ is that they experienced the rise of social media.

Millennials – Born 1980-2000 (Age 23-43)

They experienced the rise of the Internet, Sept. 11 and the wars that followed. Sometimes called Generation Y. Because of their dependence on technology, they are said to be entitled and narcissistic.

Generation X – Born 1965-1979 (Age 44-58)

They were originally called the baby busters because fertility rates fell after the boomers. As teenagers, they experienced the AIDs epidemic and the fall of the Berlin Wall. Sometimes called the MTV Generation, the “X” in their name refers to this generation’s desire not to be defined.

EDITOR’S NOTE: GenX also experienced the rise of the personal computer and this has influenced their parenting of a large portion of Millenials and GenZ

Baby Boomers – Born 1943-1964 (Age 59-80)

The boomers were born during an economic and baby boom following World War II. These hippie kids protested against the Vietnam War and participated in the civil rights movement, all with rock ‘n’ roll music blaring in the background.

Silent Generation – Born 1925-1942 (Age 81-98)

They were too young to see action in World War II and too old to participate in the fun of the Summer of Love. This label describes their conformist tendencies and belief that following the rules was a sure ticket to success.

GI Generation – Born 1901-1924 (Age 99+)

They were teenagers during the Great Depression and fought in World War II. Sometimes called the greatest generation (following a book by journalist Tom Brokaw) or the swing generation because of their jazz music.

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