By Rafael S. Lajeunesse CEO and founder of ReachX
As the advancements AI offers continue to be the talking point among various industries, there are both fears and hopes for what Artificial Intelligence could change for scale-ups and their advisors. While it’s important to consider the current limitations of AI, it’s also worth considering how AI can provide scale-ups with better advisors.
As the global economy continues to face economic challenges, it’s more important than ever for scale-ups hoping to succeed to be paired with the most suitable advisors. AI has the potential to provide extremely valuable insights for both scale-ups and advisors, as research and the abilities of AI advance.
AI can use data to provide personalised valuable insights
One of the main ways that AI is currently able to provide scale-ups with better advisors is through data. When it comes to data AI is King. Computer systems can process massive amounts of data in an extremely efficient amount of time. This data can be gathered from various sources and be personalised to your scale-up needs whether you need to evaluate your industry trends, customer behaviour, or forecast market changes. DataRobot is one automated machine learning program that helps scale-ups to use the power of AI to solve complex problems and make data-driven decisions, without requiring extensive data science expertise.
This can help scale-ups to be matched up with the most suitable investor after evaluating the most relevant data, as AI can vet advisors with a wide range of data at a fast speed. AI also helps advisors to give the most informed data-based advice based on the needs of the scale-up.
AI’s tailored and personalised advice also ensures the most relevant and effective guidance is given to the scale-up, preventing time from being wasted for both the advisors and the scale-ups.
AI can be automated and is available 24/7
Another way AI is useful for scale-ups and advisors is automation. AI-driven tools can automate data-heavy financial and operational reports. This saves time for advisors who won’t need to be bogged down in mundane number and data tasks, allowing them to focus on more specific strategic guidance and higher-level advice.
Scale-ups will also often feel like they need availability 24/7, and this is something AI can actually provide. AI-driven tools are available around the clock and can work with little to no human supervision. If an issue does arise late at night or early in the morning, AI tools can provide support without waiting for ordinary working hours.
AI can predict future outcomes for scale-ups
AI is also useful for providing insight into future outcomes for scale-ups. Predictive analytics can help scale-ups prepare for future trends and opportunities, based on predicted outcomes.
Predictive analysis can recognise risks and potential issues early on, allowing both the scale-up and advisors to resolve problems early on. The predicted outcomes can also allow advisors to recognise which scale-up they would be a better fit for, preventing constant changes in advisors for scale-ups. AI can also evaluate the best fundraising opportunities for scale-ups and set up realistic expectations.
One AI service, C3.ai, is already helping scale-ups and advisors. It delivers AI applications to help scale-ups to solve complex business challenges. Their AI suite offers predictive maintenance, fraud detection, supply chain optimization, and customer experience enhancement
AI can provide expert risk assessment
AI can also help advisors assess risks with scale-ups early on, as well as assess the risks of the advisor’s business advice. AI tools have access to a huge array of historical data and industry patterns, allowing them to provide expert advice on the risks of specific scale-ups and the decisions their advisors make. This allows both scale-ups and advisors to have confidence in their business decisions, knowing they have assessed the risks on such a large scale.
One AI-powered tool that helps advisors and scale-ups access risks is H2O.ai. It provides an open-source platform for scalable machine learning and deep learning. Their AI tools can help scale-ups to develop predictive models, gain insights from data, and make data-driven decisions across various industries.
AI can make both scale-ups and advisors more efficient
AI tools can also help advisors streamline their productivity, making their time with scale-ups more efficient, and allowing them to cater to a larger number of scale-ups simultaneously. This means they can provide a wider net of expert advice, without compromising the quality of their knowledge, making the whole process more efficient for both scale-ups and advisors.
Understanding the Limitations
It is, however, worth acknowledging the limitations of the current AI products available. AI is still arguably bad at being objective. AI systems are trained on historical data, and if this data contains certain biases, the AI can perpetuate those biases. For example, if a hiring dataset is historically biased towards certain demographics, an AI used for the hiring process may favour that demographic. This raises ethical questions about how to use AI for the hiring process and scale-ups in general.
AI is still limited in how it solves complex problems, due to its reliance on data, and its problem-solving capabilities are limited by a lack of context. As AI is subject to constantly changing regulations, it is essential to adhere to these changing rules for ethical AI usage. In short, human supervisors are certainly required to oversee the AI’s data selection capabilities to ensure fairness and unbiasedness.
In conclusion, while AI offers tremendous potential for scale-ups, it must be used with caution and awareness of its limitations and ethical implications. Continuous research and development are essential to harness AI’s power effectively while addressing these challenges and ensuring ethical and equitable usage.
About Rafael S. Lajeunesse
Rafael is CEO of ReachX and responsible for driving the company’s vision to be the trusted platform for institutional investors and corporates. Prior to founding ReachX, Rafael worked in consulting with Fortune 500 companies with McKinsey and as an investor with JJP Morgan.
