According to Stanford HAI’s 2022 AI Index, private investment in AI reached $93.5 billion – twice the total private investment in 2020. This represents the most significant year-over-year rise since 2014 (when investment between 2013 to 2014 more than doubled). Furthermore, the number of patents filed in 2021 rose to 30x greater than in 2015, marking a compound annual growth rate of 76.9%.
These recent findings prove that Jeff Bezos was right when he described the current era as a “renaissance” and “golden age” of AI. Samer Obeidat, CEO of Stallion AI, extensively discusses the AI Startup world in his book, “The AI Citizen”.
Solving problems is the core of your heart and soul as an entrepreneur. It is every entrepreneur’s drive to create solutions that tackle the most pressing challenges in the world today. With the aid of powerful AI tools like deep learning, the modern AI entrepreneur can solve these challenges in dynamic and potent ways.
However, despite the unique advantages offered by machine learning models and algorithms, an AI entrepreneur still requires a purposeful AI strategy. Here are 5 tips every budding AI entrepreneur must know to build successful world-changing solutions:
1. Data is king: Every AI model thrives on data. Still, data should not be gathered for its own sake. Clear and logical decisions and considerations must inform its acquisition. Chief among these considerations is the question – “What is the problem I am trying to solve?” Nailing down an exact answer to this question will guide your data strategy which must be drafted from the very first day. You will need to decide how to source for data and consider critical issues like data diversity and data bias to avoid creating models that work for only a particular race or gender. You also need to adopt a plan for data cleaning and data processing.
2. The user is supreme: A common mistake that many AI entrepreneurs make is to get lost in the technical details/beauty of the model that they forget the user they’re building for. Keep in mind that there is a human end-user whose opinion of your product will depend on their experience. Create a smooth user journey and rest assured that your customer retention rate will not suffer.
3. Listen to the market: While everyone wants to be ahead of the curve, it is still possible to be too early. The right solution at the wrong time can make for a frustrating entrepreneurial experience. So, it’s always best to conduct an AI Readiness Assessment of the market/industry. Is there an infrastructure available to ensure the smooth integration of the solution into the industry? Are there bureaucratic bottlenecks/policies that you might need to contend with? These are questions you want to have answers to from the start.
4. Define your expectations: You need to have a target that you are building towards. This means defining the specific, measurable, realistic, achievable and time-bound metrics by which the success of your model will be evaluated. It helps to establish a quantitative value by which an objective assessment can be made. You can then go further to communicate this with stakeholders and the users to ensure that everyone is on the same page about the capability and limitations of your AI model.
5. Use the Agile approach: Creating an AI model is a marathon rather than a sprint. There are 3 key stages – training the model, deploying the model and running the model. Working through these stages as a cycle helps to ensure that you can refine and fine-tune the process in shorter periods. The agile approach is an iterative process in which work is delivered in “small, but consumable, increments”. Many business leaders are adopting this approach now for its dynamism.
These tips are only a tiny chunk of an enormous iceberg of knowledge that can make you a successful AI entrepreneur. To learn more and qualify as a Certified AI Entrepreneur or Certified AI Professional, you can visit AIQOM AI to earn this certificate.