What are the emerging AI technologies that will shape our lives in 2024? How will AI influence the way we work and interact with each other? In what ways can businesses leverage AI to enhance customer experiences? What ethical considerations should we keep in mind as AI continues to evolve? How will AI impact education and learning methodologies in the coming year? What role will AI play in addressing global challenges such as climate change? How can individuals prepare for the changes brought by AI advancements? What are the potential risks and rewards of integrating AI into our daily routines?
AI initiatives are maturing rapidly
Let us look into several questions that have been asked in several surveys over the year 2024. Earlier this year we looked into an infographic about the perdictions in 2024.
Q. How would you best describe the criticality of AI/ML in relation to your current and future strategy?
- Minor component of a broader strategy, but it will be critical in the future.
- Single-use case in one or a few departments but is driving critical value and continues to be a major component of our strategy moving forward.
- Implemented in a few use cases/projects across a few departments that will be key for us to scale.
- Widely implemented, driving critical value, and will continue to be a major component of our strategy going forward.
Modernizing data architectures is critical to success
Q. What technological component of your infrastructure is the greatest inhibitor to your AI/ML application deployments?
- 35% Storage/Data management
- 26% Compute performance
- 23% Security
- 15% Networking
Data management and storage is the most-cited inhibitors of AI application development.
“The first thing I’ve done is doubled down on data strategy, effectively building a data platform and governance and capabilities around that. This gives us more control over our data. You’ll probably find in a lot of companies that they bolted on many of these acquisitions and have a lot of disparate systems, which means disparate data – that’s a challenge” – CIO, manufacturing/Food & beverage
Generative AI adoption is exploding
Q. In terms of your investment in AI, which of the following types of AI are you investigating as an organization?
Q. What are the primary driver(s) for developing AI/ML applications at your organization?
Organizations with GenAI as an integrated capability are seeing outstanding business impacts.
- 88% of organizations are now actively investigating generative AI
- 79% Are increasing the rate of innovation
- 76% Are supporting new product introduction
- 76% Are improving time to market
GPU cloud deployments emerging as a critical venue
Q. Which deployment venues does your organization use for inference from trained AI/ML models?
Q Which deployment venues does your organization use for training AI/ML models?
The audience answered in three categories – Edge – Near-edge – Core.
After security, the leading factor in infrastructure decision-making is accelerator availability, identified by 44% of organizations.
The adoption of sustainable data infrastructure technologies is on the rise
Q. How concerned is your organization with the impact AI/ML has on its energy use and carbon footprint?
Q. Which of the following steps has your organization taken to address the environmental impacts of your AI projects in the last 12 months?
Popular sustainability measures include:
- 64% of respondents suggested their organization was “concerned” or “very concerned” with the sustainability of their AI infrastructure.
- 42% Investing in energy-efficient IT hardware
- 40% Increasing investment in AI governance
- 37% Providing training on education and sustainability
- 35% Establishing sustainability guidelines
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