The riskier a project is, the more likely it is to fail. Risk is defined by the chance that the project will not succeed given time, costs, and quality restraints.
Glad that we have our business basics on lock! If we calculate the impact for all projects, we can group them into high- or low-impact categories already. This equals an impact of (1’000 * 10$) * 0.05 = 500$ in additional profit every month. Since we are not Amazon, a 5% increase seems reasonable. As a comparison, McKinsey states that the recommendation engine already generates more than 35% of Amazon’s revenue. We expect that a recommendation system will increase profit by 5%. Multiply these two factors together and you have a measure of impact.įor example, let’s assume you have 1’000 users who spend an average of 10$ on your website every month. You can estimate the opportunity by comparing your situation to the outcomes of competitors or your own predictions. This includes the costs to deliver the project. Opportunity addresses the expected change in financial or KPI data. Īddressable Audience is defined by how many users, employees, or produced goods are affected by a change. Impact = Addressable Audience * Opportunity. The difference between low- and high-impact AI Projects is the size of the addressable audience and the financial opportunity. How do you calculate the potential impact of AI Projects? by collecting valuable data).ĭepending on your company situation, focus on connecting impact to these three areas. Knowledge value enables employees to adopt new skills or be able to make more informed decisions in the future (e.g. Customer value focuses on driving user engagement. Business value impacts the financials of a company directly through new products or decreased costs. Tobias Grosse-Puppendahl, ex-Microsoft Researcher and now Innovation Manager at Porsche AG, differentiates three categories of value delivered by AI: business, customer, and knowledge value. Photo by James Toose on Unsplash Is all impact created equal? AI Projects should support the AI Strategy and thus the business objectives. Some companies even employ a successful AI Strategy. Every company has objectives, KPIs, or OKRs, by which it steers the business. Now, how do you assess the impact and risk of AI Projects to rank them? The following sections dive deeper into the two criteria.Īn AI Project is meaningful if it impacts the business objectives. Even if the project is successful, it will have limited impact on the bottom line. Lastly, AI Projects that are low-impact, high-risk belong to the “No-No-Never” category. It is uncertain that the project succeeds, but if your talented engineers find a way to make it work, the project promises major payoffs in return. Source: WikimediaĪI Projects that are high-impact, high-risk are considered “Calculated Bets”. The Holy Grail AI Projects everyone is looking for. If you discover these projects, hold them dearly and focus your efforts on making them work. These projects are both likely to succeed and have a major impact on business objectives. These projects can be helpful to start your AI Journey but are not relevant once your company reaches an advanced level of AI Maturity.ĪI Projects that are high-impact, low-risk, are the “Holy Grail” projects to search for. AI Projects can be clustered in four groups depending on their estimated level of impact and risk.ĪI Projects that are low-impact, low-risk fall into the “Solid Start” category. Impact defines how valuable the AI Project is, risk how likely it is to fail. The main dimensions to evaluate AI Projects are impact and risk. The insights are derived through discussions with industry-experts at Porsche AG, the Silicon Valley startup Xcalar, and my own experience. Depending on your position along the AI Maturity Journey, the trade-offs between impact and risks of AI Projects become more important. Every organization has limited resources which they need to allocate to maximize impact.
#AI PROJECT CANVAS HOW TO#
This article explains how to approach evaluating and ranking different AI Projects. Where should you start your AI Journey? How do you rank different AI Projects? What AI Projects should you focus on depending on the level of AI Maturity of your business? The private equity sector invested more than 50bn $ in AI startups in the last six years. Companies are becoming increasingly aware of the benefits of AI.
#AI PROJECT CANVAS FULL#
With a sea full of Artificial Intelligence (AI) Project ideas, it is hard to figure out where to start fishing. About the art of ranking and doubling-down on the next best AI Starship.
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