Four in ten execs don’t trust their data to generate accurate AI outputs
A new survey of C-suite executives and AI leaders reveals that while enterprise decision-makers trust the potential of AI, many lack confidence in their company’s strategy to execute and the data readiness to ensure reliable AI outputs. The survey, conducted by NewtonX for Teradata, included expert interviews and a quantitative study of executives and decision-makers responsible for AI in their roles. Despite 61 percent fully trusting AI outputs, 40 percent believe their data is not ready for accurate outcomes.
AI Strategy and Business Alignment
While 89 percent of enterprise executives believe AI is necessary to stay competitive, only 56 percent say their companies have a clear AI strategy, and just 28 percent see their AI strategy as closely aligned with broader business objectives. Most AI implementations occur at the departmental level, with only 12 percent deploying AI solutions company-wide and 39 percent implementing AI in select departments.
Key Findings:
- Trust in AI: 61% of executives trust AI outputs, but 40% doubt their data’s readiness.
- Strategic Alignment: Only 28% see AI strategies aligned with business goals.
- Departmental Deployment: 12% have company-wide AI solutions; 39% have departmental AI.
Jacqueline Woods, Chief Marketing Officer at Teradata, emphasized, “The foundation of AI is clean, reliable, trustworthy data because it is the backbone of AI outputs. While achieving complete trust remains elusive for many executives, our survey shows a deepening understanding of how to reach trusted AI at enterprise scale and confirms that Teradata is well positioned to help its customers with these business objectives.”
Benefits and Focus Areas of AI
Executives identify significant AI benefits as increased productivity (51 percent) and improved customer experience (50 percent). Despite potential in customer-facing applications, C-suite leaders prefer internal process improvements to minimize AI risks and enhance cost control.
Top Benefits:
- Productivity: 51% see substantial productivity increases.
- Customer Experience: 50% note improvements.
- Internal Processes: Focus on internal improvements to reduce risks and control costs.
About half of the executives have successfully leveraged AI for employee productivity (54 percent) and decision-making (50 percent), while fewer have used AI for product development (30 percent) or sales forecasting (30 percent).
Concerns and Challenges
More than half (57 percent) of executives are concerned about AI missteps affecting customer satisfaction or company reputation. Effective AI integration requires greater cohesiveness between AI and business planning. Executives also report using a mix of closed and public data sets (63 percent), with only 29 percent relying exclusively on closed data sets.
Barriers to Scaling AI Projects:
- Technical Talent Scarcity: 39%
- Budget Constraints: 34%
- Measuring Business Impact: 32%
- Technology Infrastructure: 32%
While 73 percent see their companies as early adopters of technology, only 27 percent believe they lead in AI adoption within their industries.
Building Trust in AI
Trusting AI projects and outcomes is critical for executives. Participants noted the importance of clear data provenance to avoid bias and emphasized that master data management is essential for reliable AI. Enhanced efficiency, successful use cases, and improved decision-making processes are crucial for fostering trust in AI.
Factors for Trust in AI:
- Reliable Outcomes: 52%
- Consistency: 45%
- Brand Reputation: 35%
Security, transparency, governance, and performance improvements are key aspects of trusted AI.
Contributing to AI Success
Primary factors contributing to AI success include clear strategic vision and leadership support (46 percent), effective communication of AI benefits (46 percent), and sufficient investment in AI technology and infrastructure (41 percent).
Success Factors:
- Strategic Vision: 46%
- Leadership Support: 46%
- Investment in AI Technology: 41%
Most respondents expect AI project results within a year (84 percent), with more than half (58 percent) seeing quantifiable results within six months. Additionally, 60 percent report demonstrable ROI from existing AI solutions.
Jacqueline Woods concluded, “There is tremendous opportunity to improve AI trust by ensuring greater cohesion between business and AI plans. But planning only gets you so far. Working with the right partners and solutions can help accelerate trust by showing accurate results and ROI from AI projects quickly. All successful AI projects start with a foundation of clean, reliable data – I call it ‘golden data’ – based on solid data sets and offering full transparency, and that’s where Teradata can help.”
Survey Methodology
The survey was distributed in the US, Europe, the UK, and Asia, polling C-suite executives and AI decision-makers in companies with at least 1,000 employees and more than $750 million in annual revenues. The survey reached approximately 300 AI-relevant executives from companies like Nike, P&G, Hermes Paris, Allianz Partners, Prudential Financial, Honeywell, and Novartis, with about half of the respondents located in the US.