Eight artificial intelligence adoption trends
Eight artificial intelligence adoption trends
Insight

Eight artificial intelligence adoption trends

Learn how some of the world’s most influential companies are transforming their organizations with AI

Nearly all business executives agree on one thing: Artificial intelligence (AI) has the power to fundamentally shift the competitive landscape.

According to KPMG’s 2019 Enterprise AI Adoption Study, technologies under the AI umbrella are already contributing to product and service improvements. And as the pace of development accelerates and spending on AI talent increases, they’ll become central drivers of future innovation, enabling enterprise-wide benefits that set tomorrow’s winning organizations apart.

Against this backdrop, business leaders face some critical questions:

“How can AI transform our business?”

“What technology and organizational capabilities should we invest in?”

“What is the right approach to strategy, risk, and governance to achieve our AI vision?” 

At KPMG, we set out to give companies a clearer view of the AI landscape by conducting in-depth primary and secondary research on the state of AI deployment at some of the world’s largest and most influential companies. Combining those learnings with insights from our work with clients on a range of AI initiatives, we uncovered eight key AI adoption trends that can serve as guideposts for enterprise transformation.

  1. Rapid shift from experimental to applied technology: The technology is now being used to address a wide range of business issues at the functional level and within lines of businesses. Although only 17 percent of companies in our study have scaled AI across the enterprise, many are setting it as a key goal over the next three years.
  2. Automation, AI, analytics, and low-code platforms are converging: Companies are finding these technologies work more effectively together, enhancing each other’s benefits and leading to better outcomes over time. They are developing structures and processes to deploy them in a coordinated and integrated manner.
  3. Enterprise demand is growing: Aiming to adopt AI more broadly across the business, many large companies are investing heavily in AI talent and infrastructure, as well as complementary capabilities to successfully deploy AI. Most companies in our study reported that they will increase their investments in AI-related talent and supporting infrastructure by 50 percent to 100 percent in the next three years.
  4. New organizational capabilities are critical: AI success requires much more than just technology. It needs the right organizational capabilities to develop and support it. While large organizations take different approaches to AI strategy, knowledge, leadership, and governance, most recognize the importance of managing organizational capital.
  5. Internal governance emerging as key area: Strong governance drives better AI outcomes, helps avoid mistakes, builds trust and credibility for AI initiatives, and creates the foundation for scale and scope. But three-quarters of companies in our sample have yet to build out true enterprise-wide governance, potentially inhibiting their ability to achieve true transformation through AI. Governance around AI includes standardizing procedures for AI monitoring, risk management, performance, and value, as well as overseeing AI technology development and the training of AI talent.
  6. The need to control AI: Without a strong control framework to monitor AI performance, risk, and compliance in real-time, companies risk AI-driven systems producing unintended results. Yet, relatively few companies—approximately 25 percent to 30 percent of companies included in our research—are investing heavily in controls that drive greater trust, transparency, and accountability in AI.
  7. Rise of AI-as-a-service: Managed services. Microservices. Bot stores. A robust AI-as-a-service marketplace is emerging that will give enterprises more options and flexibility for accessing AI capabilities. To take advantage of new delivery models, companies still need to develop an enterprise-wide AI strategy and build extensive internal capabilities.
  8. AI could shift the competitive landscape: AI projects are already paying off. Companies in our study reported a 15 percent average improvement in productivity from their AI investments. It’s no wonder many senior leaders at the world’s largest companies believe AI could truly be a game changer and that investing too little will put them at risk of falling behind—potentially permanently. Still, the level of investment in AI, the maturity of AI capabilities, and the outcomes AI has delivered vary greatly from one company to the next.
  9. Against this backdrop, an effective AI strategy should look at more than just a few narrow, functional use cases; AI should be part of broader strategic planning and viewed as a competitive differentiator. AI represents a major opportunity for companies to transform their organizations, do business in entirely new ways, and unlock new value. Read the full paper to learn more about key trends in AI adoption and how to achieve your AI vision.