The Dark Side of Cloud AI: A Controversial Look at the Industry’s Future
As the demand for powerful hardware continues to skyrocket, the revenue for AI processors is projected to increase from $4 billion in 2020 to $38 billion by 2026. But beneath the surface of this explosive growth lies a web of controversy, competition, and concern. The AI cloud market will be worth $647.60 billion by 2030, with the three leading hyperscalers, Amazon Web Services (AWS), Google, and Microsoft, vying for dominance.
The Great AI Heist
Microsoft’s exclusive partnership with OpenAI, a for-profit part of the non-profit research organization, has raised concerns about competition and data ownership. The European Commission is now preparing for an antitrust investigation into the partnership, which gives Microsoft a 49% stake in OpenAI. Meanwhile, AWS is focusing on three key services for generative AI – Amazon Bedrock, Sagemaker JumpStart, and Titan – while Google has four foundation models accessible through its Vertex AI platform: Codey, Chirp, Imagen, and PaLM.
The AI Talent Drain
The rapid growth of the AI industry has created a shortage of skilled professionals, leading to a talent drain from other sectors. "Sticking with a single model risks it becoming outdated or less effective over time," says Linda Saunders, Salesforce’s head of solution engineering for Africa. "Some of our customers are building their own models, some more successfully than others. An out-of-the-box AI model is going to get you a good bit of the way, but we still want to put the control back into the hands of the organisation."
The Cloud AI Conundrum
Deploying AI in the cloud offers numerous advantages, but comes with its own set of challenges. Katharine Janisch, head of BlueSky’s Salesforce practice, warns that clients should have a clear understanding of the AI products they’re using, especially around re-use of training data for the cloud provider, as well as data sovereignty and legislative constraints that might apply to the data being utilised. "The first rule is to always ensure that the infrastructure and cloud environments adhere to basic best practices and least privilege access control for users and service accounts," says Janisch.
The AI Cloud Trap
Cloud AI services can help democratise AI by lowering barriers to entry and enabling smaller businesses or individuals to access these powerful technologies. However, without proper economic controls, cloud AI can become costly. "Without proper economic controls, cloud AI can become costly. Pay-as-you-go is an advantage for getting quick access to AI-optimised hardware solutions in the cloud, instead of having to buy these yourself for specialised use cases," says Eugene de Souza, Red Hat’s regional cloud leader for SSA.
The AI Cloud Paradox
The AI cloud market is projected to be worth $647.60 billion by 2030, but the industry is plagued by concerns about competition, data ownership, and talent drain. "Everyone gets access to the same solution and the pricing model only changes according to the scale of your business. That creates feature and function accessibility to businesses from all walks of life," says Saunders. But is this a recipe for disaster, or a beacon of hope for the future of AI? Only time will tell.
