Enterprises are ramping up investments in artificial intelligence (AI), machine learning, and robotic process automation (RPA), with those markets set to hit $232 billion by 2025–up from about $12.4 billion today, according to a Monday report from KPMG.
However, companies still face a number of barriers to adopting these technologies and realizing their benefits, the report found, including a lack of talent, struggles defining goals and ROI, and fears on how they will impact jobs.
Here are five steps for companies to follow to improve their readiness to meet high expectations for automation technologies, according to the report.
SEE: IT leader’s guide to the future of artificial intelligence (Tech Pro Research)
1. Recognize that the use of intelligent automation is transformative, and built on the use of new machines and data sources
This means companies will need completely new plans and architectures for operating models and business models, to take advantage of these technologies, the report noted. This kind of transformation requires long-term planning, starting with prioritizing projects that can scale in one to two years. C-level support is also critical for success.
2. Formulate a comprehensive approach to automating the service delivery model
This approach should include centers of expertise, shared service centers, business partnering, self-service, and outsourcing providers, the report noted. Companies must approach automation spending across all tech platforms, while linking between other AI applications and with data and analytics. Developing solid business use cases will also guarantee investment value, and maintain expectations between deployment promises and investment ability.
3. Measure value vs. risk
The report recommends designing 2×2 structures on automation projects that show the trade-offs between preserving value and reducing risk, compared to those that are creating value and improving product and service quality. The outcome your business is seeking will determine which technology and process to select, and the speed with which to deploy them to meet specific business goals.
4. Consider the “operating model” in all forms
Operational and technology infrastructure, organizational structure and governance, and people and culture are all critical to deploying automation solutions, the report noted, and particularly on making an impact on core business processes. Implementing these technologies also means that measurements and incentive systems will need to change to align with operating model disruption.
5. Disrupt from within
Consider how to disrupt business from within while maintaining uninterrupted operations, the report recommended. For example, companies in fintech create different entity structures to continue to operate in their industry, while still disrupting.
“Companies should consider alternative investment strategies, such as divestitures and alliances, to disrupt against themselves, isolating innovation from day-to-day running of the business,” Todd Lohr, KPMG principal and US intelligent automation leader, said in the report.
The big takeaways for tech leaders:
- Enterprise investments in AI, machine learning, and RPA are predicted to hit $232 billion by 2025. — KPMG, 2018
- Businesses can follow certain steps to get the greatest benefit from automation projects, including disrupting from within and measuring value vs. risk. — KPMG, 2018