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How is AI impacting the way businesses operate?
Edward Pyzer-Knapp
Q.
Before the COVID-19 pandemic, many businesses had begun their digital transformation and were beginning to use analytics and Artificial Intelligence (AI) technologies to understand and improve their business processes. This move towards a more general position of digitisation seeded a focus on the understanding and exploitation of existing data assets. The pandemic has fundamentally altered the timescale in which this digitisation must occur to ensure the long-term productivity of most businesses.
It has also forced a paradigm shift in the complexity of the processes, which now must also consider a wealth of external information including global health and climate data to guide their strategy decisions. I believe that this transformation from a passive data-driven enterprise to an active discovery-driven enterprise, fuelled by AI and hybrid cloud, is the next major paradigm in the way businesses operate. We call this new paradigm Accelerated Discovery.
The information-driven industry will be the early proponents of the discovery-driven enterprise. Leveraging developments in NLP from Deep Learning such as transformers will enable these companies to ingest and structure the constant flow of information faster and more accurately than ever before. From this information, we will see an eruption in the development of ever more accurate digital twins of processes and structures, driven by our ability to use high-performance infrastructure to train and deploy complex AI models at scale.
This combination of the ‘real’ world and its digital twin will also enable the rapid identification of new ‘white space’ in business processes and practices. I believe that generative models will begin to help us to collaborate with our digital worlds and drive advances in computational creativity to fill in this white space with high-performing novel solutions, which can then be linked back to the real world through automated deployment by combining AI and RPA. One example we are already seeing is materials discovery. Typically, it takes 10 years and $100M to bring a material to market, but through the combination of data ingestion, AI-accelerated digital twinning, generative models, and automated experimentation we have already seen those figures fall significantly.
As AI drives our push for accelerated discovery technologies further onwards, we must remain aware of the potential to accelerate all outcomes, both good and bad. This will mean establishing guardrails and protocols to ensure that responsible advances which provide strong societal benefits are enhanced, whilst alternate applications which do not follow ethical codes of conduct are side-lined. This will require investment into the application of technologies such as explainable AI and bias detection as well as the formalisation of ethical principles for AI development .
To conclude, AI is a key component in the evolution of business from a data-driven paradigm to a discovery-driven enterprise, but we must ensure that at all stages of this transformation, we are cognizant of the potential implications of our advances, and pledge to do so responsibly.
"AI is a key component in the evolution of business from a data-driven paradigm to a discovery-driven enterprise."
Edward Pyzer-Knapp is the Worldwide Lead for AI Enriched Modelling and Simulation at IBM, Visiting Professor of Industrially Applied AI at the University of Liverpool, and the Editor in Chief for Applied AI Letters. He specializes in the interface between AI, HPC, and Scientific Discovery, and has extensive experience in developing best-in-class solutions and deploying them into real-world environments.
Edward Pyzer-Knapp
"AI is key in the evolution of business from a data-driven to a discovery-driven enterprise."
WW Research Lead, AI Enriched Modelling and Simulation
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