Enterprises See the Promise of Generative AI But Lack the Guardrails to Mitigate Operational Risks

News

1. Customer Centricity Summit & Awards Explores Brand-Customer Relationships in KSA

2. GITEX Global 2024 to Showcase Global Innovation, Investment, and Cybersecurity Trends

3. The Perfectly Imperfect Start of Disruptive Innovations

4. GovTech Conclave to Explore Cutting-Edge Solutions for Modern Governance

5. New Report Shows Cautious Optimism Among Enterprises Adopting AI

6. Majority of CISOs Feel Their Organizations are Unprepared for Cybersecurity Regulations

There is a gap between businesses’ investments in Generative AI and the ability of senior IT professionals to operationalize investments at scale. According to the Dataiku report, IT stacks across organizations are not comparable to modern infrastructure standards to maximize effectiveness and manage runaway costs. 

However, over the next 12 months, nearly three quarters of senior IT leaders (73%) plan to spend more than $500,000, and around half (46%) will spend over $1 million in Generative AI initiatives.

The report found that most agreed the proliferation of disconnected tools, lack of tech optionality, and outdated processes will intensify current challenges, such as data quality, governance, and risk management:

• Nearly half of respondents (44%) indicated that their current data tools do not fit their analytics and AI needs, and 43% reported that their current data analytics stack needs to meet modern infrastructure standards. Another 88% do not have specific tools or processes for managing LLMs. 
• Over three-quarters of IT leaders agree that modernizing their data stack means adding AI capabilities, followed by tool consolidation (65%).
  
• A majority of IT leaders (60%) said they use more than five tools to perform each step in the analytics process, from data ingestion to MLOps and LLMOps. Another 71% want five or fewer tools to reduce the burden of scaling projects with cobbled-together systems. 
• Lack of governance and usage control can compound operational risk. A worrying portion of respondents (74%) still rely on spreadsheets for quick analyses, even as 62% have faced serious issues due to spreadsheet errors.
  
• Data quality and usability remain the biggest data infrastructure challenges that IT leaders face (45%), even with the many tools in their data stack. With data access issues cited by 27% of respondents, organizations still have not solved the data quality problem.  
  

“The reality is that Generative AI will continue to shift and evolve, with different technologies and providers coming and going. How can IT leaders get in the game while staying agile to what’s next?” said Conor Jensen, Field CDO of Dataiku.“All eyes are on whether this challenge — in addition to spiraling costs and other risks — will eclipse the value production of Generative AI. Our survey reveals most data stacks are not built to meet these needs.”