Data Complexity Report Highlights Challenges and Opportunities for AI Adoption
2025 is shaping up to be a defining year for AI, as organisations transition from experimentation to scaling their AI capabilities. However, businesses are facing mounting challenges, including data complexity, security, and sustainability. According to NetApp’s latest Data Complexity Report, businesses are making significant investments to drive innovation and efficiency, but these efforts will only succeed if global tech executives can address these pressing issues.
Cost of Transformation
Two-thirds of businesses claim their data is fully or mostly optimised for AI purposes, highlighting significant improvements in making data accessible, accurate, and well-documented. However, the report reveals that the journey towards AI maturity requires further significant investment. A striking 40% of global technology executives anticipate "unprecedented investment" will be necessary in 2025 just to enhance AI and data management capabilities. While considerable progress has been made, achieving impactful breakthroughs demands an even greater commitment in financial and infrastructural resources.
Data Silos Impede AI Success
One of the principal barriers identified in the report is the fragmentation of data. An overwhelming 79% of global tech executives state that unifying their data, reducing silos, and ensuring smooth interconnectedness is key to unlocking AI’s full potential. Companies that have embraced unified data storage are better placed to overcome this hurdle. By connecting data regardless of its type or location, they ensure constant accessibility and minimise fragmentation.
Scaling Risks of AI
As businesses accelerate their AI adoption, the associated risks – particularly around security – are becoming more acute. More than two-fifths of global tech executives predict a stark rise in security threats by 2025 as AI becomes integral to more facets of their operations. AI’s rapid rise has expanded attack surfaces, exposing data sets to new vulnerabilities and creating unique challenges such as protecting sensitive AI models.
Limiting AI’s Environmental Costs
Beyond security risks, AI’s growth is raising urgent questions of sustainability. Over one-third of global technology executives predict that AI advancements will drive significant changes to corporate sustainability practices. Meanwhile, 33% foresee new government policies and investments targeting energy usage. The infrastructure powering AI and transforming raw data into business value demands significant energy, counteracting organisational sustainability targets.
Conclusion
In conclusion, NetApp’s Data Complexity Report highlights the pressing issues faced by organisations as they strive to optimise their strategies for AI success. To achieve AI maturity, businesses must address the mounting challenges of data complexity, security, and sustainability. By prioritising data unification, robust security, and environmental responsibility, organisations can drive innovation while ensuring resilience and responsibility in the new AI era.
FAQs
- What are the key challenges facing organisations in adopting AI?
- Data complexity, security, and sustainability are the primary challenges.
- How can organisations overcome these challenges?
- By prioritising data unification, robust security, and environmental responsibility.
- What is the cost of transforming to an AI-driven organisation?
- A striking 40% of global technology executives anticipate "unprecedented investment" will be necessary in 2025 just to enhance AI and data management capabilities.
