While the overall adoption of Artificial Intelligence (AI) has remained steady in recent years, the latest McKinsey Global Survey on the state of AI in 2020 has found that business value derived from AI solutions is on the increase, especially coming in the form of new revenues. That’s good news in these times of unprecedented uncertainty that have forced businesses of all sizes to re-evaluate their business models and operations to survive.
According to the McKinsey report, in many cases, AI has made a significant difference this past year, with companies planning to invest even more in the technology in 2021, “in response to the COVID-19 pandemic and acceleration of all things digital.”
Below, we look at some of the outcomes of McKinsey’s survey, starting with the report’s key high-level findings:
- 50% of respondents said their companies have adopted AI in at least one business function.
- AI adoption is highest in the product-development or service-development and service-operations functions.
- 22% of respondents said that at least 5% of earnings before interest and taxes (EBIT) were attributable to AI.
- Revenue increases from AI adoption were more commonly reported in half of the companies surveyed with cost decreases less common.
According to the McKinsey report, “companies seeing the highest bottom-line impact from AI exhibit overall organizational strength and engage in a clear set of core best practices.” To help better understand how they achieved this, the researchers at McKinsey outlined the six sets of practices that differentiate higher-performing companies from the rest, including:
- Strategy: Leading companies typically have a clear vision and strategy with a strong C-level commitment, as well as a road map for AI initiatives that is linked to business value across the organization.
- Talent and leadership: Credible AI leaders, tailored training for existing employees, and effective recruiting of new AI talent are all qualities of leading companies identified in the McKinsey survey.
- Ways of working: Investing and risk-taking, advanced deployment teams and processes, and a framework for governance are all ways leading companies are evolving around working with AI.
- Models, tools, and technology: Standard practices for developing AI models, automated testing tools, and standardized, end-to-end platforms are all ways leaders keep AI initiatives consistent across the business.
- Data: A clear data strategy with proper protocols on quality, data generation processes, and well-defined governance processes ensure data integrity, security, and availability.
- Adoption: Implementing capabilities designed for scalability, putting in processes to get from pilot to production, and tracking key performance indicators help keep AI initiatives at leading companies on track and executable.
To learn more, including actual best practices reported by executives from the survey and case studies by industry, check out the complete McKinsey Global Survey report.