Evgeny Grigul is its co-founder Virto Commercea B2B-first e-commerce innovation platform for businesses.
AI is an infrastructure technology that significantly affects various aspects of our reality. In this article, we’ll look at how AI may impact the technology adoption curve for digital products and what it means for investors who are currently applying the technology adoption curve to their work.
What is the technology adoption curve?
The technology adoption curve, popularized by Everett Rogers in his book Diffusion of Innovationsshows how different segments of the population adopt new technology at different rates. This is the basic empirical principle used to predict how new technologies are adopted today.
The technology adoption curve describes the process by which the market adopts innovations. According to this principle, the public is categorized into five groups: innovators, early adopters, early majority, late majority, and laggards.
Innovators and early adopters are the first to embrace new technologies, often driven by curiosity and risk tolerance. The early and late majority represent the larger, more cautious segment, adopting once the technology is proven. Laggards are the last adopters, often resisting change.
Why do investors rely on the technology adoption curve?
Understanding this curve helps businesses adjust strategies for each phase, from product development and marketing to scaling and mainstream adoption. It has significant implications in areas such as marketing, product development and overall business strategy.
Investors use the technology adoption curve to assess the potential success and timing of investments in startups and emerging technologies. It helps them make informed decisions about when and where to allocate capital based on the expected adoption and development trajectory of a product or innovation in the market.
The adoption curve helps investors assess the scalability of a product or technology. They assess whether a company’s business model aligns with its position on the curve, examine how quickly a technology is moving through the adoption curve to predict how it will disrupt existing industries or markets, and use the adoption curve to diversify their portfolio across various stages of adoption technology.
Ultimately, venture capitalists use the adoption curve to help plan their exit strategy. Investments made in the early adopter phase may be withdrawn once the company reaches early majority and achieves significant market traction, allowing the investor to sell at a high valuation. On the other hand, entry during the early majority phase can lead to exits based on profitability and scale.
The technology adoption curve is also widely used by different experts such as product managers, IT leaders and CIOs, marketers, business planners, strategy executives and others. They used to rely on the principle of the adoption curve and didn’t see a world where it didn’t work. But AI would dramatically change the game.
How is artificial intelligence going to disrupt the technology adoption curve?
One of the factors slowing technology adoption is the user adoption problem. The transition to new technology presents challenges due to the need to retrain users to work with a new interface, which causes difficulties and resistance, ultimately slowing the spread of the technology.
The traditional approach to designing user interfaces is based on the idea that the user must learn to “explain” the task to the software or device using a language that the machine can understand. At the most basic level, this refers to programming languages. For end users, this usually means a user interface, which can also be considered a type of language. To use a new product effectively, users must learn and master this language. This requirement often becomes a barrier to the adoption of new technologies.
AI, however, can help enable a new paradigm in which the responsibility of “translating” commands shifts to software rather than users. Instead of training users to work with a new interface, the AI allows them to formulate tasks in the way they are used to, and the AI will be responsible for deciphering and accurately interpreting those tasks.
For many software products and services, adopting a new paradigm can be revolutionary. The transition from the old technology to the new will be virtually seamless, as users will be able to start using (and therefore benefit from) the new technology immediately after launch.
This also means a reduced role for the interface as a competitive advantage. With the new approach that puts the responsibility of understanding user commands on artificial intelligence, the customer experience will not change significantly when moving from one vendor to another. All of these will affect the applicability of the technology adoption curve in describing reality and the quality of decisions that take the curve into account. I expect we can predict the following consequences.
First, I believe we can expect the adoption of the technology to accelerate significantly. AI-based systems can reduce adoption frictions by making complex products easier to use. AI also allows products to be highly personalized from the start, which can attract early adopters, providing them with immediate value.
We can also expect a blurring of boundaries between different groups or a change in numerical proportions between them. This will likely lead to a radical change in the dynamics and predictability of new technological products in the market, requiring new approaches to working with them.
Here are seven key points for investors to consider regarding the impending disruption of the technology adoption curve:
1. A faster adoption rate means new technologies can reach market viability faster, leading to an increase in startups offering innovative solutions.
2. Accelerating the adoption curve may require re-evaluating exit strategies.
3. With faster adoption, time from investment to exit (via acquisition or IPO) can be reduced.
4. As technologies gain traction faster, competition among venture capitalists for promising startups may intensify.
5. Rapid adoption can change the risk profile of investments.
6. Investors may need to adapt their due diligence processes to account for the rapid nature of technology adoption.
7. Rapid adoption can lead to rapid changes in the market, where established players may be quickly disrupted by new entrants.
As such, AI is set to fundamentally reshape the technology adoption curve, accelerating adoption rates and lowering user barriers. As AI redefines the user experience, investors and businesses must prepare to navigate a faster and more unpredictable adoption landscape.
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