Chemical companies are exploring the potential of Artificial Intelligence (AI) and machine learning to optimize day-to-day operations, create enhanced customer experiences and develop innovative products—while improving operational efficiency and reducing costs. Examples include using AI to simulate processes to support product development, as well as for maintenance and “smart plants.”
Research among 1,000+ early adopters of AI shows chemical companies’ usage of AI is advancing: 61 percent have gone beyond the pilot stage to start implementing machine learning or other forms of AI, and 91 percent strongly/agree that machine learning-enabled processes help them realize previously hidden value.
Chemical companies that have taken the plunge are seeing big benefits—72 percent report a minimum 2x improvement in some process KPIs, and 37 percent a 5x improvement.
Three interrelated dimensions
As explained further in the book Human + machine: Reimagining work in the age of AI written by Accenture’s Paul Daugherty and H. James Wilson, leaders across industries harness three interrelated dimensions of AI:
- Reinvent processes: rethinking standardized processes as continuously adaptive and applying AI to manage process change.
- Utilize data: using AI and data to solve previously unsolved problems and reveal hidden patterns.
- Rethink human-machine collaboration: shifting toward an AI-enabled culture and reskilling employees to collaborate with machines.
Only 7 percent of chemical companies—versus 10 percent cross-industry—are doing all three systematically. And they’re developing capabilities in these areas at different speeds:
- 17 percent systematically apply AI to reimagine processes.
- 31 percent harness data plus AI to capture exponential improvements.
- 45 percent are rethinking how humans and machines collaborate.
Successes to date
In terms of reimagining processes, one chemical company is using a digital tool combining advanced robotics with image technology to predict the performance of marine coatings. Another company plans to fly drones to inspect its plants. And, another is using data science to determine successful leadership attributes.
Chemical companies are relatively more advanced than other sectors in using AI to rethink the human/machine relationship. This reflects the importance of worker safety in the chemical sector as one of the main benefits of AI implementations to date is safer operations—for example, by reducing the need for human maintenance visits to hard-to-access areas.
Key focus areas
As they build on advances to date, three focus areas will be key for chemical companies to realize the full benefits of reimagined processes:
- Customer: exploring the potential of intelligent virtual agents, for internal use and customer service desks.
- Asset: creating an “intelligent plant” utilizing cognitive learning for predictive insights.
- Worker: helping employees collaborate with machines to augment their capabilities.
Challenges to overcome ...
Chemical companies’ use of AI will grow rapidly. But challenges must be overcome, including the segregation of operational data (currently run by plants).
Another barrier is investment. Chemical companies think in terms of “big bang” capital projects. To fully embrace AI, they need a radical culture shift, with IT/OT organizations becoming much nimbler.
…opportunities in the “missing middle”
AI can help solve another challenge—the aging workforce. First, it can help educate existing employees on how to pivot to the new. Second, AI facilitates the capturing of knowledge by getting experienced workers to teach smart machines.
In the book, Human + Machine, the authors discuss other opportunities to empower people and machines to collaborate in the “missing middle”—the spectrum of human/machine alliances where each enhances the other. This includes using machines to augment humans with data-driven insight. Humans can also train AI technologies like chatbots and Robotic Process Automation (RPA).
Four steps to take
How can chemical companies prepare for a future enabled by reimagined processes? Take four steps:
- Define what AI, machine learning and reimagined processes really mean for the industry.
- Explore the feasibility of reimagining processes through design thinking.
- Consider the workforce and AI to be complementary, not competitors.
- Develop an integrated source of data.
Chemical companies have made a measured, rather than rapid start to their AI journey. But as reimagined processes emerge, the pace of progress will accelerate.