2022. 08. 22-23 In-Person and OnlineACS Fall 2022
Penn Club of New York
30-W 44th St, NY
11:15 am - 12:00 pm
12:00 pm - 1:00pm
1:00 pm - 2:00 pm
Check for early-bird rates
The role of artificial intelligence (AI) in business and the global economy is a hot topic. This is not surprising, given recent progress, breakthrough results, and demonstrations of AI, as well as the increasingly pervasive products and services already in wide use. All of this has led to speculation that AI may usher in radical–arguably unprecedented– changes in the way people live and work. However, AI is not a single technology but a family of digital tools and techniques, e.g., computer vision, natural language, virtual assistants, robotic process automation, and advanced machine learning. Chemical companies will likely use these tools to varying degrees. Some will take an opportunistic approach, testing only one technology in a specific function. Others may be bolder, adopting all five and then absorbing them across their entire company.
Recent cross-industry research conducted by the McKinsey Global Institute (MGI) suggests that AI technologies could lead to a substantial performance gap between the front runners on one side and slow adopters and nonadopters on the other. At one end of the spectrum, front runners (i.e., companies that fully absorb AI tools across their enterprises over the next five to seven years) are likely to benefit disproportionately. By 2030, they could potentially double their cash flow (economic benefit captured minus associated investment and transition costs), which implies additional annual net cash flow growth of about 6 percent for more than the next decade. Front runners tend to have a strong starting digital base, a higher propensity to invest in AI, and positive views of the business case for AI.
Large firms have a competitive advantage in adopting and absorbing AI ahead of industry peers. MGI’s econometric simulation suggests that they have good adoption rates. In fact, early corporate adopters will benefit from the exponential impact, potentially gaining many more benefits than followers. This discussion focuses on how AI could affect the chemical industry’s business processes and the innovative business models that the industry leaders must adopt to thrive in this fast-changing environment.