Vultr and S&P Global Market Intelligence unveiled a new industry report, The New Battleground: Unlocking the Power of AI Maturity/MultiModel AI. This groundbreaking, industry-wide research is unique in that 72% of the 1,000 decision-makers surveyed represent AI-driven organizations that have reached higher levels of AI maturity.

In the transformational stage – the most advanced level of maturity – 32% of companies have integrated AI into their core business processes and view it as a significant value generator for their customers. In the accelerated stage, 40% of companies are deploying AI extensively, with numerous daily applications. Finally, 27% of companies, classified in the operational stage, have started incorporating AI into some of their daily operations. (Only 1% of survey respondents fell into the experimental phase.)

Any company with AI ambitions can learn much from this report – not only from the decisions mature AI organizations are making regarding spending, infrastructure, and deployment strategies, but also from their business outcomes and future plans.

Here are a few of the key findings:

AI’s impact on business performance: You get what you put into it

Transformational organizations are winning hearts, minds, and shares of wallets – not to mention improving their operating margins. These AI trailblazers report outperforming their peers more than those at lower stages of maturity – 50% of them are significantly” outperforming operational-stage organizations. They also have greater expectations for growth across all outcomes measured.

However, nearly all companies with at least some AI deployed say their 2022/2023 year-over-year performance improved across all core business metrics. Any business that wants to catch up must invest now to accelerate AI models, training, and scaling in production – bearing in mind that 49% of the organizations surveyed expect moderate to significant increases in AI spending next year.

With AI, there is no room for standing still.

It’s a multi-model world

The number of models actively used within an organization says much about a company’s AI maturity level. On average, organizations across all maturity levels have 158 models in production, which is expected to hit 176 models within the next year.

Organizations that continually build on their AI capabilities will likely experience enhanced operational efficiency and competitive advantage. Those that don’t won’t.

AI must be core to all you do

Not only do 89% of organizations expect to deploy advanced AI within their organizations in two years, but 80% of organizations will adopt AI across all business functions.

We are in a new, pervasive AI order. It’s no longer about building and training models but rebuilding all apps with AI at their core. Organizations must integrate all the principles of cloud engineering and CI/CD pipelines before layering in AI.

It’s no longer enough to be cloud-native. Organizations must be AI-native.

The tech behind the triumphs

Achieving AI maturity demands a new technology class with an open, composable stack and platform engineering as its bedrock. 88% of the enterprises surveyed intend to increase their AI spending next year to support their crucial infrastructure strategies as follows:

• In 2025, the AI infrastructure stack will be a hybrid cloud,with 35% of inference taking place on-prem and 38% in the cloud/multi-cloud.
• For cloud-native AI applications,two-thirds of organizations are either custom-building their models or using open-source models to deliver functionality.
• Open, secure, and compliant are the top attributes of cloud platforms for scaling AI across the organization, geographies, and to the edge.
• 80% of survey respondents expect to grow their AI edge operations in the near future.

AI specialists: More valuable than traditional cloud providers

Among the survey’s most eyebrow-raising reveals: 47% of AI-driven organizations report partnering with an AI specialist (25%) or global system integrator (22%) to help them with strategy, implementation, and deployment of AI at scale. Only 15% are turning to traditional hyperscalers.

This makes sense. As enterprises look to achieve greater AI maturity, a new infrastructure order is forming that doesn’t rely solely on traditional hyperscalers, whose baggage – unpredictable costs, limited GPU availability, finite scalability, sketchy security/privacy, vendor lock-in, etc.–is becoming too hard to ignore.

Businesses need an alternative cloud platform that supports their core cloud data engineering, AI workloads, and hybrid architectures – one that provides all the security, compliance, and core services needed to rebuild cloud infrastructure with AI at the core of every application.

Contact our sales team to learn more about how Vultr brings the vision, strategy, technology, and expertise to help the AI-aspiring become mature AI powerhouses.

For a full copy of the report, click here.