The age of artificial intelligence (AI) is here, and countries in the Asia Pacific (APAC) and Middle East zones have set their eyes on the prize. Start-up activity around AI is booming, and the region is set to overtake the rest of the world in AI spending over the next three years — reaching $15 billion by 2022, according to IDC.
Against this backdrop, we surveyed 590 senior executives across the region in late 2019 to understand their companies’ AI plans and actions. Our goal was to learn how APAC and Middle East businesses are employing AI, how this emerging technology is impacting business and how they are overcoming challenges to reap value from machine intelligence across various functional areas. (To learn more about the study, including its methodology, see our white paper, “How Companies Can Move AI from Labs to the Business Core.”)
While our research was conducted before the outbreak of COVID-19, we believe the pandemic only underscores the urgency around implementing AI — and doing so thoughtfully. Advanced forms of AI are critical to our understanding and treatment of infectious disease. Machine learning (ML) and deep learning are helping infectious disease scientists more quickly sequence and model treatment therapies and vaccinations, accelerating time-to-market and limiting unintended consequences. They are also helping researchers more effectively forecast and foretell the contours of pandemics. These capabilities are applicable to every business in every industry.
Despite significant progress, AI’s impact in APAC and the Middle East is today limited by the fact that businesses remain in experimentation mode (see Figure below). If this is a cloud, there is indeed a silver lining: organisations in the region can learn from the hard-won experience of businesses elsewhere. With this in mind, we prescribe the following procedures to shift AI from experimental mode to production mode.
Deploy AI tools and algorithms in line with the maturity curve.
At a given point in time, any two organisations will confront different problems and challenges. Achieving AI maturity involves moving along the maturity curve iteratively, adopting the necessary tools and creating new algorithms. Appropriate options will be defined by where organisations find themselves on the digital maturity curve.
Pave the way for creating an AI-centred culture.
The cultural rewiring of a business begins at the top and should be approached with the end goal of becoming a data-driven organisation in which human creativity thrives around AI. To that end:
Inculcate cross-functional cooperation. To realise AI’s transformative power, businesses need a cross-functional team and a structured approach to identifying opportunities for process improvements.
Overcome risk aversion. As businesses move beyond experimentation, they will need an environment that encourages creativity and a risk-taking attitude. To make this happen, we recommend setting up an AI office or centre of excellence to oversee AI projects from ideation to production. Small, multi-skilled teams are critical. AI success depends on combining knowledge from business functions, processes, data and technology.
Close the learning loop. Bridging the gap between learning from AI experiments, which happens simultaneously across the business, and the areas in which the lessons can be applied is important for advancing capabilities. An organisational mechanism that can oversee the experiments and update the broad approach accordingly can go a long way in upgrading capabilities.
Keep on communicating. A strong culture thrives on communication. AI deployments might succeed or fail, but communication keeps people going. It is critical for any corporate AI effort to keep all channels open for sharing knowledge and information.
To learn more, visit the AI section of our website or contact us.