CONSHOHOCKEN, PA — Boomi™ has teamed up with MIT Technology Review Insights to release an insightful report titled “A Playbook for Crafting AI Strategy.” This comprehensive study provides an in-depth look at the current state of AI adoption among enterprises and offers actionable strategies for navigating the evolving landscape of artificial intelligence.
Businesses are eyeing ambitious AI milestones, with predictions like PwC’s forecast that AI could add $15.7 trillion to global GDP by 2030. However, significant challenges remain in moving from pilot projects to full-scale AI deployment. For instance, only 5.4% of U.S. businesses used AI to produce a product or service in 2024, reflecting a need for strategic and organizational changes to fully leverage AI.
Key Insights from the Report
The report highlights several trends and challenges in AI adoption:
1. Limited Scale Beyond Pilots: While 95% of companies surveyed currently use AI and 99% plan to in the future, most are still in the pilot phase. Only 24% have scaled AI beyond three use cases. This year is crucial for laying the groundwork for widespread AI deployment, as half of the companies aim to integrate AI across all business functions within two years.
2. Increased AI Spending: AI-related spending in 2022 and 2023 was mostly modest or flat. However, this is expected to change in 2024, with nine out of ten respondents planning to boost spending on AI readiness, which includes platform modernization, cloud migration, and data quality improvements. Four in ten companies expect a 10-24% increase in spending, while one-third anticipate a 25-49% rise.
3. Importance of Data Liquidity: Seamless access to and analysis of data from various sources is crucial for effective AI deployment. Data liquidity eliminates the need to sift through massive data repositories by ensuring that relevant information is readily available.
4. Data Quality Issues: Half of the respondents cited data quality as the biggest barrier to AI deployment. This issue is particularly pronounced in larger firms with extensive data and legacy IT infrastructure. Companies with over $10 billion in revenue are most likely to report data quality and infrastructure challenges.
5. Cautious AI Adoption: Almost all organizations (98%) prefer to delay AI implementation to ensure it is delivered safely and securely. Governance, security, and privacy concerns are the main factors slowing AI deployment, cited by 45% of respondents.
“Over the last year, organizations have come to understand the power and potential of AI,” said Matt McLarty, CTO at Boomi. “This year, those organizations are seeking to shift from small pilots to enterprise-wide deployment of AI at scale.”
Strategies for Successful AI Deployment
The report offers several guiding principles for companies looking to advance their AI initiatives:
1. Building AI Foundations: Establishing a solid data foundation is essential. Companies are investing in data quality, data liquidity, and IT infrastructure to meet their AI goals.
2. Targeted AI Use Cases: The most valuable AI applications are those that drive specific, business-relevant outcomes. While general-purpose AI tools are easy to implement, they are also accessible to competitors. Unique use cases that provide a competitive edge are more beneficial.
3. Financial and Partnership Considerations: In 2024, AI costs—from GPUs to talent and energy consumption—must be factored into ROI measurements. Forming partnerships with the right vendors and tools will be crucial for most companies’ AI futures.
4. Risk-Moderated Adoption: Organizations are cautious about AI risks and prefer a measured approach over being first movers. An evolving regulatory environment and a better understanding of AI risks will likely accelerate adoption.
“The biggest factor holding back AI implementation is not knowing where to start,” added McLarty. “You don’t actually have to be an expert on how to create generative AI in order to get value from generative AI.”
With its latest report, Boomi aims to guide businesses through the complexities of AI strategy formulation, helping them harness AI’s transformative potential effectively.
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