Navigating the AI On-ramp
The AI Outlook to 2030
AI has entered a critical acceleration phase. While we may be able to visualise the longer-range outcome, where AI is all around us and automating much of it, the next steps that we will take to get there are harder to understand.
The range, speed and profound nature of the changes underway make it hard to see much beyond the next couple of years.
This is the AI On-ramp.
This analysis explores that on-ramp by drawing together a comprehensive view of the trajectory of AI technological advancement, the penetration into business and society. It begins to examine the fundamental shifts in data architecture that will be required, and the emerging constraints that will shape the way ahead.
It is based on extensive analysis of current trends and authoritative research, not least the publication in late May of analysis by the highly respected Mary Meeker.
Contents:
The decision-makers’ challenge
Executive Summary and Key Insights
1 – The Evolution of AI and its use through 2030
2 – The Implications for Data
3 – Navigating the Constraints and Choke-points
4 – Timeline
Appendix 1 – Glossary
Appendix 2 – Key Research Sources
Read or download the papers
- Navigating the AI On-Ramp – the entry point to the subject, since it’s these aspirations that are driving the whole agenda
- Making Data Fit for AI – the implications for data because AI without the right data is as much use as a chocolate fireguard
- The Latest Infrastructure Trends – the days of infrastructure as a limitless, on-demand resource are long gone
- The Future of AI Data – what “data” actually is, is changing rapidly, with large implications
- SEO is Dead – much attention focuses on content creation by AI, but what does it do for the audience?
- AI and Data Glossary – I’ve tried to keep jargon to a minimum, and this is a list of those that needed to be included
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| Peter G. Osborn [email protected] +44 (0)7802-666758 https://www.peterosborn.com |