“Both the people and the culture you build are key. You won’t build an innovation-driven culture by implementing advanced technologies alone”
Mark Sheldon
CTO, SIDE TRADE
“We’ve seen huge progress in the innovation of AI technology over the last decade or so. We’re now at a point in the cycle where the winning AI innovators stand out from the crowd, and we’re seeing an increasing amount of mainstream adoption of its applications. In the coming future, the usage of AI technology will be commonplace such that the hype will eventually fade away.”
In the forthcoming years, two technologies stand out with the biggest future impact, both of which are at two very different stages in their innovation cycle:
The first is AI and its subsets, Machine Learning (ML) and Natural Language Processing (NPL). We’ve seen huge progress in the innovation of AI technology over the last decade or so. We’re now at a point in the cycle where the winning AI innovators stand out from the crowd, and we’re seeing an increasing amount of mainstream adoption of its applications. In the coming future, the usage of AI technology will be commonplace such that the hype will eventually fade away.
The second technology is at a much earlier stage in the innovation cycle when compared to AI. According to my prediction, “the next big thing” is Quantum Computing. It is predictable to see incredible breakthroughs from this technology and specifically in the field of Quantum Machine Learning (ML), where the current bounds of binary computing and training data limitations will not exist anymore. I expect this will push AI into the second wave of innovation, and the cycle will start all over again.
The drivers & disruptors for the technology innovations
For traditional AI & ML technology, we’ve already passed the early innovation phase, so the key driver moving forward will be in building companies, products and services that have already been established and have proven their success in increasing their mainstream adoption and commercial applications of the technology.
Therefore, the focus now needs to fall on implementation into new areas, deployment, re-training (aligned with the AI-Ops movement) and the governance and ethics surrounding the reality of AI in the real world. The scenario is different for Quantum Computing, which is at a much early stage in the innovation cycle than AI. We’re now at the point where funding and support for emerging projects, companies, and research is imperative. I think we’ll see the most value for driving innovations forward, especially once the established technology providers make the new hardware more accessible.
Aggressive adoption of advanced technologies for staying relevant and competitive
It is undoubtedly clear that most successful business organizations innovate. Adopting advanced technologies is a key ingredient for staying relevant and competitive. There needs to be a focus on the business objective to ensure businesses don’t just innovate for innovation’s sake. I see so many companies that invest millions to build predictive models on their data but deliver nothing into production nor provide any additional value to their customers or shareholders through their innovation.
Firstly, it’s equally important to find a product-market fit with your innovations, a well-known trend in the start-up world. Still, in my opinion, it should also apply to all businesses looking forward to innovating or implementing advanced technologies. Secondly, both the people and culture you build are key. You won’t build an innovation-driven culture by implementing advanced technologies alone. As the world tackles a problematic pandemic and a widening digital skills gap, businesses must invest further in their employees, look past the hype of formal academic training, and better hone their recruitment skills to spot the right talent (either already skilled or those with great potential) for their business.
