Accelerating Venture Building processes with AI: Implications and Responsibilities
September 11, 2023
I am pretty sure it is not the first time you read the word AI today. Suddenly, we are flooded with information about “how to make X better with AI”, to the point we have agreed that this is the new paradigm we will surf in the near future. It is undeniable that AI has implications beyond our understanding, and humanity needs to be ready to regulate and digest an unpredictable number of changes. As mentioned by Harari in the Lex Friedman podcast, AI is the first tool that empowers itself, instead of us. Reason why uncovering better ways to cooperate is a subject of research for every industry today.
Our industry is known for being required to manage immense amounts of data to generate a new venture concept to scale. We have built methodologies that allow us to do Market, Problem, and Solution Discoveries to obtain the best way to profit from a defined territory. However, “Psychologists say that humans can handle four independent variables and when we get to five, we’re lost” (Harvard Gazette, 2020). Our big efforts to structure all this data has been beyond human capabilities, and nowadays we have the opportunity to do so with the required tools. But, what should we expect and how do we prepare?
The world is not going to end next week, and business builders still have a lot to say
AI won’t take over our reality, and ChatGPT won’t substitute you – for now. The recent discoveries of how many things can get done in seconds with an accurate prompt has brought the industry to an uncomfortable spot. Suddenly, our insecurities arise and we see this alien tech put together information that it would take us days to gather, in a split of a second.
All of a sudden, all those outputs we have cherished for years are magically done, and are good enough to continue down the path our methodology suggests. All those hours dedicated to generating outputs – hours that we use to estimate the value of our work – result in meaningless and leave us stranded in the middle of a generational switch where we need to reevaluate how we understand our industry, and where does the actual value we provide come from.
Thus, we can either fear or embrace it, and as the Board of Innovation mentioned: “AI won’t replace innovators. But Innovators who use AI will definitely replace those who don’t”.
We need better Humans, not less technology - Kasparov
Understanding where the value of our work comes from is the key to adapt to this new generational switch. After years where the output was the most important part of the process, now focus has casually gone back to ‘craft’. This ‘human-centered’ approach is understandable, but we are missing out on the cooperation opportunities that AI brings forward, allowing us to focus on the human-side of building a business, and delegating the most data-heavy, research-demanding part of it.
Correctly executing a Problem Discovery (in my opinion the cornerstone of the whole venture building process) requires all business builders to empathize with the users that belong to the territory. Sometimes the meaning of the words they use is not the real message they want to transmit, and we need to look underneath their skin to grasp the value in their words fully. This ability is a natural human superpower, hard to teach to machines at current stages of development.
In order to extract this level of information from a user we can heavily rely on AI tools to generate the artifacts that will allow us to ask the right question, and iterate the output to match our needs. This level of cooperation will help us deliver quicker, and once we achieve the desired output, we can reintroduce it into the AI tool to generate whatever we need next.
By normalizing the relationship with AI and actually using it as a pseudo-member of the team (Our favorite Junior Business Builder), we understand that it can actually automate and execute many time-consuming tasks that will free-up space from the Business Builders minds: optimizing resource allocation by analyzing data and making informed decisions, identify areas where resources can be maximized, such as optimizing marketing budgets or identifying cost-saving opportunities in operations, or even how to exploit any code – this is a much creepier example that we will not get into now, but worth a quick Google check.
But what do we need to understand before we fully introduce AI in our processes?
Garry Kasparov wonderfully put aside his ego when he said: “Few people in the world know better than I do what it’s like to have your life’s work threatened by a machine”. However, he moved on and proposed collaboration rather than competition. Corporate Venture Building is still years away from being taken over by AI, since reading the context is a need to build any business. AI algorithms process vast amounts of data and can churn out insights based on patterns. However, they lack the human ability to perceive context. Understanding the context is still an ability that belongs to us, that now can be further empowered through AI tools.
Therefore, let’s make sure we understand some key ideas that gather the points stated before:
> Value Identification:
Recognize that while outputs can be generated by AI, the true value in a business building often lies in the human-centric process.
> Human Empathy vs AI Data Processing:
Machines can analyze data and patterns, but they cannot empathize or truly understand the subtle nuances of human behavior and motivation.
> AI as a Tool, Not a Replacement:
AI should be seen as a supplementary tool to aid human abilities, not as a complete replacement. It can automate data-heavy tasks but cannot replicate human intuition and judgment – yet.
> Data Quality:
The efficiency and accuracy of AI-driven decisions depend on the quality of the data fed into the system. Inaccurate or biased data can result in misleading insights.
> Collaboration Over Competition:
Instead of viewing AI as a threat, it’s essential to perceive it as a collaborative force that, combined with human capabilities, can revolutionize the way businesses operate.
> Ethical and Contextual Considerations:
AI lacks moral judgment and contextual understanding. Decisions based solely on AI might not consider the broader ethical or contextual implications.
We’re at a transformative crossroad. With the potential of AI’s data-driven insights combined with the depth of human expertise, we can craft ventures that are not only profitable but also deeply connected with human needs and values. In order to do so there are many variables that need to be considered: data quality, feedback loops, prompt generation to extract the ideal output… variables that we will get better at overtime by solely practicing and introducing these tools in our daily life.
All in all, regardless of us being at a unique point in time where the industry can strongly grow and accelerate its production by leveraging new, still uncomprehended tools, the secret ingredient of a business still belongs to us and our ability to read between the lines and perceive what other people feel and need. The world is about to change, but we are about to adapt to new ways of doing that will unlock the next ‘that’s the best idea ever!’ kind of moment.
Trust the process.