AI in SaaS: A Different Kind of Bubble

Executives who understand its potential are already adopting an “AI-first approach”, weaving it into dev operations, analytics, and productivity. For others (in their own 'bubble'), AI is merely another trendy buzzword (crypto/NFTs..) or else they are still dragging their feet to commit dev resources in AI related experimentation. If you find yourself in the latter group, consider this your wake-up call.

Facts:

• Sequoia's study (June 2023) indicates that "94% of companies in their network already utilize a foundational model API, and 65% having AI applications in production"

• Gartner recent survey (July 2023) revealed "55% of Organizations That Have Deployed AI Take an AI-First Strategy..".

Top 5 use cases I've observed SaaS enterprises experimenting with:

1) Code Assistance & Bug Detection

2) Contact Center Automation

3) Analytics & Data Science Copilots

4) Sales and Marketing

5) Enhancing Work Productivity with AI Assistants

Conclusion: I believe sooner the teams start experimenting with AI solutions to find a good match to a SaaS organisations' requirements (secure/auditable/maintainable/talent/cost..), sooner you can drive value. One thing is clear there won't be one solution that fits all.

References:

1. https://www.sequoiacap.com/article/llm-stack-perspective/

2. https://www.gartner.com/en/newsroom/press-releases/2023-07-27-gartner-survey-finds-55-of-organizations-that-have-deployed-ai-take-an-ai-first-strategy-with-new-use-cases 

If you've made up your mind to experiment with AI solutions, and evaluating whether to rent or build? Then you might find this relevant: