How can your business advance its AI initiatives to actual ROI? The clock is ticking

The clock is ticking for organizations to create significant and sustained value through their generative AI initiatives, according to the latest State of Generative AI in the Enterprise research from Deloitte. The report identified key ways that companies can move from potential to performance including: 

Also: Businesses can reach decision dominance using AI. Here’s how

• Building success on initial success: Improved efficiency, productivity, and cost reduction are still the top benefits sought by organizations. Those are also cited by 42% of respondents — 2,770 enterprise leaders — as their most important benefits achieved to date. And 58% reported realizing a more diverse range of important benefits, such as increased innovation, improved products and services, or enhanced customer relationships.
• Strive to scale: Two of three surveyed organizations said they are increasing their investments in generative AI because they have seen strong early value. Yet nearly 70% of respondents said their organization has moved 30% or fewer of their generative AI experiments into production
• Modernize data foundations: Three-quarters of respondents said their organizations have increased investment around data life cycle management to enable their generative AI strategy. Top actions include enhancing data security (54%) and improving data quality (48%). However, data issues still negatively impact progress — 55% of organizations reported avoiding certain generative AI use cases because of data-related issues.
• Mitigating risks and preparing for regulation: Organizations feel far less ready for the challenges that generative AI brings to risk management and governance — only 23% rated their organization as highly prepared. In fact, three of the top four factors holding organizations back from developing and deploying generative AI tools and applications are risk, regulation (such as the European Union’s AI Act), and governance issues.
• Maintaining momentum by measuring: More than 40% of respondents said their companies are struggling to define and measure the exact impacts of their generative AI initiatives. 

Here are 10 key takeaways of Deloitte’s report:

1.  Most businesses are increasing their investments in generative AI: Given the strong value seen to date, 67% of organizations said they are increasing investments in generative AI. Most are citing benefits beyond productivity, efficiency and cost reductions — 58% include benefits such as increased innovation (12%), improved products and services (10%), and enhanced customer relationships (9%).
2. Business leaders care deeply about AI: Survey respondents said that interest in generative AI remains “high” or “very high” among most senior executives (63%) and boards (53%).
3. Scaling AI adoption in the enterprise must be a priority: However, many generative AI efforts are still at the pilot or proof-of-concept stage, with a large majority of respondents (68%) saying their organization has moved 30% or fewer of their generative AI experiments fully into production. A large majority of organizations have deployed less than a third of their generative AI experiments into production
4. The essential elements for scaling generative AI initiatives from pilot to production include (I’ve bolded the elements that I believe matter most): 
   – Clear, high-impact use case portfolio
   – Ambitious strategy and value management focus
   – Strong ecosystem collaboration 
   – Robust governance
   – Agile operating model and delivery methods
   – Integrated risk management
   – Transparency to build trust in secure AI
   – Transformed roles, activities, and culture
   – Acquiring external and developing internal talent
   – Modular architecture and common platforms
   – Modern data foundation
   – Provisioning the right AI infrastructure
   – Effective model management and operations 
    
5. The obstacles for generative AI adoption and scaling is legacy technology: Technology infrastructure (45%) and data management (41%) fared the best, followed by strategy (37%), risk and governance (23%), and talent (20%).
6. Do organizations think they are ready for generative AI? No. Readiness by category — technology infrastructure (45%), data management (41%), strategy (31%), risk and governance (23%), and talent (20%). All AI projects start and end as data projects so these readiness numbers are alarming. 
7. Businesses are investing more in data life cycle management: 5% of organizations have increased their technology investments around data life cycle management due to Generative AI.
8. Levels of concern in data management are high: Using sensitive data in models (57%), managing data privacy-related issues (58%), managing data security-related issues (57%), complying with data, governance (49%), using company proprietary data in models (38%). A data trust layer is key to the successful deployment of generative AI solutions. Data-related issues have caused 55% of the organizations we surveyed to avoid certain generative AI use cases.
9. The top three barriers to successful development and deployment of generative AI tools and apps are risk-related: Worries about regulatory compliance (36%), difficulty managing risk (30%), and lack of governance models (29%). Only 23% rated their organization as highly prepared to manage risks.
10. Measuring value in AI investments is difficult but doable: According to Deloitte’s survey results, 41% of organizations have struggled to define and measure the exact impacts of their generative AI efforts. Some enterprises reported employing formal approaches to measure and communicate generative AI value creation, including using specific KPIs for evaluating generative AI performance (48%) and building a framework for evaluating generative AI investments (38%). It is worth noting that although a majority (54%) of organizations are seeking efficiency and productivity improvements, only 38% reported they are tracking changes in employee productivity. And only 35% track return on AI investments. 

Also: 1 in 3 workers are using AI multiple times a week – and they’re shouting about it

The research found that only 16% of organizations reported they produce regular reports for the CFO about the value being created with generative AI. Smart technology leaders know this: There are no IT projects, there are only business projects. Investment, deployment, and adoption of AI must be measured based on business outcomes — and it should go beyond productivity and cost-cutting objectives. The best use of technology is to improve the quality of life and work — for your employees, customers, business partners, and communities that you serve. 

To learn more about Deloitte’s State of Generative AI in the Enterprise report, you can visit here.