Artificial Intelligence (AI) Strategy

An Artificial Intelligence (AI) Strategy is an IT strategy that is focused on AI technologies.

• Context:
  • It can (typically) address Organizational AI Technology Decision, such as AI investment decisions.
  • It can (often) be summarized in an AI Strategy Document.
  • It can (often) align with an Organizational Digital Transformation Strategy (e.g. to drive innovation and improve efficiency).
  • It can (often) encompass:
    • AI Talent.
    • AI Ethics.
    • AI Tech Investment.
    • ...
  • It can (often) include an AI Technology and Capability Roadmap.
  • It can (often) references a Data Strategy.
  • It can range from a High-Level AI Vision to being a detailed AI Roadmap (with specific AI projects and AI timeline)s.
  • It can (often) involve identifying AI Use Cases (across different business functions or industry verticals).
  • It can (often) have a position on AI Capability development (such as ML capabilities, NLP capabilities, or computer vision capabilities).
  • …
• Example(s):
  • an AI Technology-Specific Strategy, such as:
    • a Recommender System AI Strategy, for recommender systems.
    • a Machine Learning (ML) Strategy, for machine learning technology.
    • an LLM Strategy, for large language models technology.
    • a Chatbot AI Strategy, for AI chatbots.
    • a Machine Translation (MT) Strategy, for machine translation technology.
    • a Computer Vision AI Strategy, for computer vision technology.
    • a Voice Recognition AI Strategy, for voice recognition technology.
    • a Fraud Detection AI Strategy, for fraud detection technology.
    • a Robotics Automation AI Strategy, for robotics automation technology.
    • an AI Agents Strategy, for AI agents technology.
    • ...
  • a Company-Specific AI Strategy, such as:
    • Amazon's AI Strategy, such as Jeff Bezos's 2010 one, which focuses on leveraging AI for improving customer experience and operational efficiency.
    • Google's AI-first Strategy, emphasizing AI's central role in product development and company direction.
    • Microsoft's AI Strategy with a focus on integrating AI into its Azure cloud services.
    • IBM's Cognitive Computing Strategy, ...
    • LegalTech Company AI Strategy, such as a LegalTech LLM strategy.
  • …
• Counter-Example(s):
  • an Operational AI Plan.
  • a Data Strategy, Cloud Computing Strategy, or Network Security Strategy, which may include AI elements but is focused on the broader goal of securing organizational networks against threats.
• See: Digital Transformation, AI Governance, VP of AI.

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References

2023

• ChatGPT.
  • An Artificial Intelligence (AI) Strategy can typically reference the latest trends and predictions for AI, such as those in 2023:
    1. Generative AI Growth: The 2023 McKinsey Global Survey highlights the explosive growth of generative AI (gen AI) tools. A significant number of organizations are already using gen AI regularly in at least one business function. C-suite executives and board members are increasingly incorporating gen AI into their strategies, with a focus on investment in AI overall due to advances in generative AI 32†source.
    2. AI Disruption and Reskilling: Gen AI is expected to cause substantial business disruption, leading to workforce changes such as cuts in some areas and extensive reskilling efforts to address evolving talent needs 33†source.
    3. AI Adoption Across Functions: Gen AI is being used in functions like marketing and sales, product and service development, and customer care, suggesting that organizations are targeting areas where AI tools offer the most value 34†source.
    4. Risks and Challenges: Despite the rapid adoption, many companies are not fully prepared for the risks associated with widespread gen AI use. Key concerns include mitigating inaccuracy, cybersecurity, and regulatory compliance 35†source.
    5. AI High Performers and Diverse Applications: Organizations that achieve significant value from AI, known as AI high performers, are utilizing AI across more business functions than others, particularly in product and service development, risk, and supply chain management. These high performers are also leveraging AI in HR and other areas for optimization and development 36†source.

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