Will AI/ML Cross the Chasm?
Exploring how leadership's risk tolerance impacts competitive advantage and growth for companies and markets.
The recent release of OpenAI’s ChatGPT has raised a lot of questions about the impact of AI on businesses, employees, and work efficiency. The platform’s ability to complete text when prompted a question or topic, improve code, and generate images produces an almost nuclear fusion-like capability: produce more output than input into the reaction- enabling smarter, faster, more efficient, and creative work. This begs the question, is this the first time we have been able to leverage artificial intelligence and machine learning (AI/ML) to do this? The answer as I have been reminded by an expert in this field is a sharp “NO”. In his experience at several Fortune100 companies, over the past decade, similar capabilities were being leveraged by some companies such as Amazon & Google and sidelined as “unnecessary” or “less accurate than existing strategic frameworks/business methodologies” by others. Naturally, this prompted more questions as to why ChatGPT has garnered so much public interest, can it break through adoption barriers and what will be its reach into mainstream use by companies and individuals?
In 2017, I was working at a startup biotechnology company specializing in next-generation sequencing (NGS) products to help scientists explore the genome. While the first NGS instrument by Lynx Therapeutics Company became available in 2000, trailing ~3 decades of prior work behind it, the technology was still rather new to most researchers in academia and industry. Many users were comfortable with using traditional methods such as multiplex PCR or Sanger-based approaches or preferred to buy NGS products from already-established suppliers. Working through the launch and growth of our products, I was confronted with a set of similar questions.
Why did some scientists we approached with our new products were willing to try it, while others did not?
What is the opportunity cost of maintaining the status quo vs. trying and possibly failing by switching to new alternatives?
When & how should companies manage displacement of old methods with new more advanced alternatives?
How to communicate/promote the value of new over old?
How to define and calculate the cost of avoidable lost opportunities when the current methodologies still work?
My boss recommended that I read Geoffrey A. Moore’s Crossing the Chasm: Marketing and Selling Disruptive Products to Mainstream Customers to learn about the drivers and barriers in product/technology adoption. A great recommendation. Since then, I have applied the concepts in the book blending with some of my own to 3 companies - with success.
Moore highlights 5 categories of technology/product adopters: Innovators, Early Adopters, Early Majority, Late Majority, and Laggards. Adoption is influenced by the adopter’s risk appetite and receptiveness to change, making the Innovators more risk tolerant and willing to try and fail versus the Laggards that are more risk averse and tend to operate on a “wait and see” model to leverage the failure of those before them pave a safer path for their experience. “Crossing the Chasm” is referring to the turning point to entering mass adoption (Figure 1). For any new technology or framework to successfully cross the chasm, it would require the mainstream to buy into the product/technology. This requires adoption and promotion by the Innovators and the Early Adopters first, then convincing the rest to engage. The book then explores how these decision makers engage with and influence this process.
Figure 1: Crossing the Chasm by Geoffrey Moore
My recent conversation about OpenAI reminded me to revisit crossing the chasm on both micro (company) and macro (market) levels. Let’s start here:
Companies are made up of decision makers in leadership positions.
Markets are made up of companies with decision makers who work for them.
This means these decision makers have micro and macro impact on how technologies/frameworks are adopted at their organizations and their collective markets. It’s obvious that executives/leaders must create and protect competitive advantage for their company; however, how does their risk appetite/adoption style impact their company’s ability to defend their market position and enable faster growth? As I imagine you have encountered this at your organization in the past or present and undoubtedly will at some point in the future (it’s just the law of probability), most executives/decision makers fall in the Early Majority, Late Majority, and Laggards categories, taking on less risk in adopting new technologies for the companies they lead. This may result in loss of competitive advantage, compounded by the pressure coming from the companies whose leaders fall in the first two categories. Early adopters have the potential to capitalize on their lead time to prepare their companies for bigger wins. If you think about it, generally, company leaders are rewarded for being stable and consistent thinkers and decision makers, trained to take less risk on applying non-mainstream approaches. While these characteristics and approaches tend to produce forecastable and consistent growth, it may result in losing the advantage to capitalize on opportunities. For example, see quarterly revenue for 3 major companies Amazon, Walmart and Target (Figure2). While Amazon heavily invested in AI, other companies pursued more traditional (e.g M&A, brick & mortar growth) approaches to gain market share. As you can see, Amazon was able to leap to close the gap against Walmart.
Figure 2: Quarterly revenue data on Walmart, Amazon, and Target 2009 - 2021.
The enthusiasts, visionaries, and the pragmatists are less risk averse than the conservatives and laggards. Building on Moore’s model, there is an inverse relationship between risk appetite and competitive advantage (Figure 3). The Innovators and Early Adopters have a “competitive advantage” that becomes less available to the remaining categories over time. Essentially, time is of the essence when it comes to adopting new technologies & frameworks that advance business position and grow market share. The compounding effect of timely action or inaction can make or break companies and markets. Additionally, the cost of lost revenue & market share, due to lack of action to respond to market indicators, may be masked by the steady growth generated by the more traditional approaches (Figure 2: Walmart vs. Amazon). The hidden danger of becoming stale/obsolete is more costly than a few failed experiments.
Figure 3: Adoption risk tolerance and competitive advantage
So what can you do about it at your organization?
Grow a culture of meritocracy, masterfully explained in The Principles by Ray Dalio, to select the best idea and promote a culture of excellence not rank.
Promote experimentation, enabling Innovators and Early Adopters to evaluate and adopt new technologies and data-driven frameworks in their organizations and as a result the collective industries. This can be done by establishing an incubator for research, where new ideas can be explored, vetted, and considered for development and implementation. This reduces risk of massive failures and enables companies to stay ahead of the competition by having an array of levers to pull quickly and as needed.
If you are not a decision maker/leader, as John F. Kennedy asks, “be the change you want to see in the world” to apply these concepts in your area and share learnings and wins with others. This will inspire others to join you and grow the culture over time.
Going back to our opening question, can OpenAI ChatGPT and AI/ML in general cross the chasm? I would suggest YES. In recent years, Innovators and early adopters who have leveraged the earlier versions of these tools/methodologies have demonstrated their potential and return on investment (RoI) in real-world scenarios. The mainstream now has an opportunity to engage with and integrate AI/ML into marketing & communication, code QA, creative design, etc., to reduce cost, increase productivity, and gain competitive advantage. Companies who invest in these technologies will have an opportunity to experiment and establish their presence and gain time/advantage on their competitors to increase operational efficiency and create new product/market opportunities.
Would love to hear your thoughts on this topic. Feel free to comment here or reach out via email.