CEOs must determine what AI means to their businesses
- Data providers are turning to AI to protect and grow core revenue while pivoting to new adjacent growth.
- Technology vendors are placing big bets on AI as the basis of their future businesses.
- Commercial enterprises are implementing AI and data-driven solutions.
It’s essential that data business CEOs “stay ahead” so they can capitalize and not get caught by disruption
- Thought leaders struggle to stay current with the quickly evolving technology landscape and vendors.
- CEOs must make smart choices by identifying the right business models and use cases to get started.
- Chief executives need to be “eyes wide open” as AI has a network effect, opening up new types of competition.
To help data and information businesses develop a sound AI strategy, this study will
- Define AI to get beyond the hype.
- Outline how AI is part of the analytics continuum, to enable better decision-making.
- Exemplify AI transforming data into actionable insights and enabling greater scale.
- Illustrate how the AI technology landscape has changed and who and what to pay attention to.
- Highlight AI use cases that create new value in enterprise domains and industries.
This study combines:
- Synthesis from Outsell’s daily contact and interviews with CEOs, CDOs, CPOs/CTOs and heads of analytics and decision-making data businesses.
- Deep knowledge of Outsell’s ongoing and unique 20+ years of market analysis
- Original analysis based on the deep industry experience of our analysts
- Assessment of technology vendors’ public disclosures and earnings
It also draws upon our unique discipline of studying the major information market components (data/content, technology, and workflow) that, when triangulated, add 360-degree context to our insights into how businesses view, capitalize, and evolve their data and product strategies with AI.
Table of Contents
Why This topic 3
OUR Methodology 4
AI definition and getting beyond the “Buzz” 5
The AI Market landscape has expanded 13
Core Foundation (AI technology and Data Services) 15
Example: Enabling Immersive Customer Experiences 17
Example: Extracting Meaning an New Insights from Content 18
Example: Leveraging AI an the Cloud to Scale the Business 19
Advancing Functional Applications for the Enterprise 20
Embedding AI in Legacy Portfolios 21
Example: Improving Behavioral Targeting 22
Example: Optimizing Situational Advertising 23
AI is an Enabler for IoT and Vice Versa 24
Advancing Industry solutions for the Enterprise 25
Industry Use Case Examples 26
AI having a Profound Effect on the Financial Sector 27
Example: Amassing New Insights and Predictions in Financial Services 28
Example: Advancing Scientific, Patient Care an Drug Discovery 29
Example: Innovations in Legal Solutions 30
Key Takeaways 31
Essential Actions 32
Related Research 34
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