Few emerging fields of technology have generated as much excitement in recent years as AI. Artificial intelligence (AI) promises to be one of the most disruptive classes of technologies over the next 10 years. This is in large part driven by advances in computational power, the volume, velocity and variety of data, as well as in deep neural network (DNN) methods, natural language processing (NLP) technologies, a connected globe and accelerating returns. AI methods and technologies are posed to bring transformative change to societies and industries world-wide.
The game-changing nature of AI and its role as a major driver of innovation, future growth, and competitiveness are internationally recognized.
Beyond productivity gains, AI also promises to enable humans to develop intelligence not yet reached, opening the door to new discoveries. This includes high impact discoveries within the domains of Healthcare, Circular Economy, Education and Social Entrepreneurship.
To take advantage of AI in a real and sustained way, startups, enterprises and ecosystem parties need to develop solid strategic & operational plans for the following essential elements; data and analytics (D&A), the necessary infrastructures, methodologies for getting started and ethics and governance.
Market value AI 2026 $202.6 Billion (up from $20.7B in 2018)
Global GDP 2030 +14%
AI Top 4 Fastest Growing Startup Sub-Sectors in Early Stage Funding Deals
AI Top 2 Startup Exit Growth over the past 5 years
Organizations are gearing up their multidisciplinary teams to implement a variety of AI techniques in ever more business areas. Depending on the AI Maturity level and AI Readiness organizations will have specific requirements for AI solutions, knowledge and skills. Maturity Is a Critical Enabler for Scaling AI. As AI maturity increases, its capabilities in key areas will also mature. Which capabilities are relevant depends on the actual and expected AI business use-case categories.
Organizations should identify and prioritize their main AI business use-case categories and required capabilities as early as possible. Preferably, this process should be based on a sound AI strategy aligned with an overall data and business strategy.
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