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Cost of Transformation
Two-thirds of businesses worldwide claim their data is "fully or mostly optimised" for AI purposes, highlighting significant improvements in making data accessible, accurate, and well-documented. However, the study 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. Catching up with AI’s potential might not come cheap, but leaders prepared to invest could reap significant rewards in innovation and efficiency.
Data Silos Impede AI Success
One of the primary 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 (across hybrid multi-cloud environments), they ensure constant accessibility and minimize fragmentation. The report indicates that organisations prioritising data unification are significantly more likely to meet their AI goals in 2025. Nearly one-third (30%) of businesses failing to prioritise unification foresee missing their targets, compared to just 23% for those placing this at the heart of their strategy.
Scaling Risks of AI
As businesses accelerate their AI adoption, the associated risks – particularly around security – are becoming more acute. More than two-fifths (41%) 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. Countries leading the AI race, including India, the US, and Japan, are nearly twice as likely to encounter escalating security concerns compared to less AI-advanced nations like Germany, France, and Spain. However, progress is being made. Despite elevated concerns, the report suggests that effective security measures are yielding results. Since 2023, the number of executives ranking cybersecurity and ransomware protection as their top priority has fallen by 17%, signifying optimism in combating these risks effectively.
Limiting AI’s Environmental Costs
Beyond security risks, AI’s growth is raising urgent questions of sustainability. Over one-third of global technology executives (34%) 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. AI-heavy nations often feel the environmental impact more acutely than their less AI-focused counterparts. While 72% of businesses still prioritise carbon footprint reduction, the report notes a decline from 84% in 2023, pointing to increasing tension between sustainability commitments and the relentless march of innovation. For organisations to scale AI without causing irreparable damage to the planet, maintaining environmental responsibility alongside technological growth will be paramount in coming years.
Conclusion
In conclusion, the report highlights the pressing issues faced by organisations globally as they strive to optimise their strategies for AI success. To overcome the challenges of data complexity, security, and sustainability, businesses must invest in unified data storage, robust security measures, and a clear understanding of how data evolves. By doing so, they can drive innovation while ensuring resilience, responsibility, and timely insights in the new AI era.
Frequently Asked Questions
Q: What are the primary barriers to AI success?
A: Data complexity, security, and sustainability are the key challenges faced by organisations in their AI journeys.
Q: How can businesses overcome data silos?
A: By unifying data, reducing silos, and ensuring smooth interconnectedness, organisations can unlock AI’s full potential.
Q: What are the scaling risks of AI?
A: Security threats, particularly around data protection, are becoming more acute as AI becomes integral to more facets of operations.
Q: How can businesses mitigate environmental costs associated with AI?
A: By maintaining environmental responsibility alongside technological growth, organisations can scale AI without causing irreparable damage to the planet.
