In this unprecedented era of technology-driven transformation, it becomes more critical than ever that we aggressively invest in developing robust artificial intelligence (AI) for wargaming in support of decision-making. By advancing AI-enabled systems and pairing these with human judgment, we will be able to enhance all-domain awareness, improve the speed and quality of our decision cycles, offer recommendations for novel courses of action, and more rapidly counter our adversary's actions. It therefore becomes imperative that we accelerate the development of AI to help us better address the complexity of modern challenges and dilemmas that currently requires human intelligence and, if possible, attempt to surpass human intelligence--not to replace humans, but to augment and better inform human decision-making at machine speed. Although deep reinforcement learning continues to show promising results in intelligent agent behavior development for the long-horizon, complex tasks typically found in combat modeling and simulation, further research is needed to enable the scaling of AI to deal with these intricate and expansive state-spaces characteristic of wargaming for either concept development, education, or analysis. To help address this challenge, in our research, we are developing and implementing a hierarchical reinforcement learning framework that includes a multi-model approach and dimension-invariant observation abstractions.

The best use cases for AI in the last one year were found in combating the effects of the pandemic. The healthcare industry built numerous applications of AI for faster diagnosis, forecasting the spread and pattern of the disease, tracking people and their recovery, developing drugs, vaccinations, and managing the logistics. Supply chain and retail companies have used AI and cognitive automation to overcome the threats of Covid-19, as consumers faced significant challenges in shifting from physical to online mode. Besides healthcare and retail, businesses of all shapes and sizes across several sectors have adopted AI to pursue higher productivity and enhanced customer experiences. However, managing the entire charter of an organisation gets tough as AI permeates through a multitude of functions.

Key quote "The life sciences industry has only begun to scratch the surface of AI's potential but the good news is biopharma and life sciences leaders see the potential and are willing to make the investments necessary to realize what's possible. They should be cautious, though, and carefully plan and strategize so those investments are used wisely and result in the desired outcomes. By spending time on a solid strategy, putting the building blocks in place for success and leveraging relationships with relevant partners, AI can help transform the life sciences industry as we know it and get the necessary products to market more quickly." Why this matters From R&D to manufacturing, supply chain to commercial functions, AI is beginning to have an impact on increasing efficiencies across the biopharma value chain, especially as a result of the COVID-19 pandemic. In addition, increased remote work environments helped life sciences leaders realize how effective digital solutions can be in helping their businesses run smoothly, transforming mindsets and enabling executives to lean into a future grounded in digitization, data and AI.