What You Should Know:
– To provide valuable industry insight, Deloitte has released its State of AI 5th edition research report, which surveys global business leaders and executives on how businesses and industries are deploying and scaling AI.
– The report includes valuable insights into the healthcare sector’s current successes in deploying AI, including where companies are working to enhance processes around a patient’s journey.
Fuelling the AI Transformation: Four Key Actions Powering Widespread Value from AI
The AI market continues to advance rapidly, and leaders across industries consistently report how important this technology is to their future. In fact, in our most recent State of AI in the Enterprise survey 94% of business leaders reported that AI is critical to success over the next five years. Yet challenges persist in achieving outcomes at scale.
Since 2017 Deloitte has been tracking the advancement of AI across industries through surveys of global business leaders. The fourth edition of the report pivoted to look at the wide
set of leading practices needed to scale AI across an enterprise and achieve meaningful results. With the fifth edition, Deloitte advances that journey, digging deeper into additional actions and decisions that can lead to outcomes—or middling results.
Key findings and insights from the survey are as follows:
1. This year’s survey found that, unfortunately, many organizations are struggling with middling results, despite increased deployment activity. Seventy-nine percent of respondents reported achieving full-scale deployment for three or more types of AI applications—up from 62% last year. Yet, the percentage of respondents that now find themselves in the Underachievers category (High deployed / Low achieving) rose to 22% this year from 17% last year
2. 76% of respondents reported they plan to increase their investments in AI to gain more benefits. Increases are slowing slightly (down from 85% who planned increased investment in 2021) indicating that funding may be leveling off after the last few years of significant increase. However, very few respondents (3%) reported a decrease in investment.
3. Survey respondents reported varying challenges depending on the stage of AI implementation. When starting new AI projects, the top reported challenge is proving AI’s business value (37%). As organizations attempt to scale up their AI projects over time, key impediments such as managing AI- related risks (50%), lack of executive buy-in (50%), and lack of maintenance or ongoing support (50%) push toward the top of the list.
4. Interestingly, 87% of respondents reported that they are now finding the length of payback period to land within their expectations or faster. While on the one hand this indicates an increased understanding of implementation requirements, it could also suggest that the vision for AI may be too focused on cost savings, and that the transformational opportunities that AI can offer, which often have less predictable timelines, are being overlooked or ignored.
The report also discussed the 4 actions leaders should consider in order to improve the outcomes of their AI efforts:
Action 1: Invest in culture and leadership. The workforce is increasingly optimistic, and leaders could do more to harness that optimism for culture change, establishing new ways of working, and to drive greater business results with AI. 82% of respondents surveyed indicated their employees believe that working with AI technologies will enhance their performance and job satisfaction.
Action 2: Transform Operations. An organization’s ability to build and deploy AI ethically and at scale largely depends on how well it has redesigned operations to accommodate the unique demands of new technologies.
Action 3: Orchestrate tech and talent. Technology and talent acquisition should no longer be considered separate. Organizations should strategize their approaches to AI based on the skill sets they have available, whether they derive from humans or pre-packaged solutions.
Action 4: Select use cases that can help accelerate value. Selecting the right use cases to
fuel an organization’s AI journey depends largely on the value drivers for your business, influenced by your sector and industry context. Learn about some of the top use cases driving change for your industry.