Looking Ahead Expect major AI investments from a diversified buyer pool, including sovereign funds, venture capital funds, and even major tech corporations, who look to maintain an upper hand on the competition by incorporating new generative AI and machine learning technologies. That said, there are a few risks in the pipeline: • Higher Initial Costs: 50% of executives have cited costs as the largest hurdle to their company’s AI implementation. Costs related to infrastructure, data collection and AI talent acquisition can be daunting for startups and SMBs. Experts have estimated that it takes 18 months on average to fully implement AI projects, which can pose a significant risk for risk-adverse companies that may be operating with a tight budget. • Increased Regulations: Data privacy, misinformation and cybersecurity risks spur increased regulations for AI. Recently, the National Institute of Standards and Technology passed the Federal Artificial Intelligence Risk Management Act of 2023, which directs federal agencies to use an Artificial Intelligence risk management framework. • Need for Private AI: AI algorithms are trained to use customer information, causing data privacy concerns. Industries in the public sector, life sciences, and financial services will look to minimize data breach risk by limiting public AI usage and search for vendors who can offer private AI. Public AI valuations are at all-time highs — Microsoft, Apple and Nvidia all recorded market caps of over $3 trillion in 2024, driven by major technological advancements in the industry. Maintaining rapid growth will hinge on an enterprise's ability to accommodate increased regulation. This is notable around data privacy, which will spur an opportunity for AI companies to implement private AI. Overall, we expect AI to continue benefiting the global economy, as organizations across the globe continue to implement AI to increase productivity, achieving tasks with more accuracy and at a faster rate.
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