Upcoming Events
Fri, Feb 9th: 🧠 GenAI Collective 🧠 Let's Talk AGI! 🤖
🗓️ Hungry for even more AI events? Check out SF IRL, MLOps SF, or Cerebral Valley’s spreadsheet!
If you didn’t get a chance to listen to our most recent episode of the Collective Intelligence Community Podcast, go listen to our very own Thomas Joshi and Stephen Campbell’s interview with the CTO of Twelve Labs Aiden Lee where they dive into their founding story and the AI revolution in video understanding.
For this issue, we are thrilled to feature a fellow community member Anish Chadalavada, the co-founder and COO of Gradial, who provides his thoughts on how emerging startups will disrupt end-to-end workflows to capture enterprise value.
Enhancing Enterprise Value with Generative AI
The Current State of Generative AI
Generative AI is quickly becoming a cornerstone for new innovation, with AI-native applications spawning in every business function and industry. Much of the early focus has been on generating text, but enterprises are increasingly seeking unified solutions that can handle workflows downstream of text creation to realize true ROI. For example, startups writing marketing content, sales emails, and support messages have gained early funding and traction. Yet, enterprise adoption remains relatively low due to unproven ROI and an inability to solve end-to-end workflows. Many early AI tools solve an acute pain point but haven’t shown a measurable impact on reducing costs or increasing revenue.
According to Menlo Ventures 2023 generative AI report, enterprise executives cite “unproven return on investment” as the biggest barrier to adoption. To be successful and unlock enterprise users, generative AI platforms will need to offer something that moves past the status quo to:
Show real ROI by helping businesses drive end-to-end workflows that are today a combination of software, humans, and processes. For example, increasing the volume of outreach emails, leads or blog posts is not enough. Companies must show conversion rates that improve the bottom line, or automations that directly reduce costs.
Integrate deeply with existing enterprise software systems of record that businesses use and trust. Enterprises live in systems like Salesforce, Adobe, and Workday. Without connecting to these systems, many startups struggle to break through the ROI barrier as they don’t have all the context needed to build a world-class solution.
The Road to Success for Generative AI Platforms
In 2024, we expect more startups (and incumbents) to expand their offerings across the capability chain to support entire enterprise workflows with AI—starting with integrations to trusted enterprise systems of record. One of the key implications of a renewed focus on ROI is the role of incumbents. In some cases, incumbents will win by deeply embedding their application within their existing system(s) of record (e.g., Microsoft Copilot). In other cases, startups will offer the better solution, but they will still need to integrate with the incumbent system of record, as this is where enterprise users, workflows, and data live today. Startups can still win by providing a better experience to end users. Many workflows today require interoperating across different systems and teams. Unifying these in a single AI-enabled experience can create a truly differentiated product.
We are already beginning to see this evolution underway in conversations with leading enterprises:
Content creation → end-to-end content lifecycle management (publishing, updating, analyzing, and redesigning content) in an enterprise’s CMS or DAM system.
Cold email writing → end-to-end outreach campaigns that help sales teams gather leads, write personalized emails, surface the insights that matter, and automatically update their Salesforce CRM.
Support chat bots → end-to-end support experience that intelligently routes requests, responds automatically where possible, unifies the support rep and chatbot experience, and logs interactions in the enterprise system of record.
Moving Beyond Basic Content Creation
Nowhere is the shift more evident than in content creation. Within enterprise functions, marketing has traditionally been an early adopter for both technology and generative AI as it is a competitive space and public facing content typically doesn’t rely on sensitive information. In the last 12-18 months, businesses like Jasper and Writer scaled quickly by helping marketers get to a first draft of content much quicker than before.
However, as AI-generated content proliferates, users are questioning how different such tools are from just using ChatGPT. Brands are starting to think more about how to differentiate themselves with personalized content, and how to serve and iterate on that content at a faster pace. For enterprises, this requires an AI-enabled workflow that goes beyond content creation to support the entire content management lifecycle. This includes native integrations into CMS systems like Adobe or Drupal. Emerging startups like Gradial are at the forefront of this evolution by helping businesses make content updates or redesigns instantly based on data-driven analysis. These platforms automatically surface the most engaging content across different audiences, so brands can continue to push the highest performing AI- and human-generated content to create a data-driven, personalized, and highly flexible marketing strategy.
As language models continue to improve, enterprises will continue placing a premium on workflow solutions with provable ROI rather than point solutions that struggle to move past the co-pilot stage. Rather than buying tools that enable faster drafts of blog posts, they will want platforms that truly drive differentiated digital experiences and personalization at scale across the entire content creation lifecycle: content creation, publishing, and continuous iteration based on the metrics that improve the conversion of MQLs. The best AI companies will meet enterprises where they are to transform entire workflows and drive tangible results.
We would love to hear how the community sees the next generation of generative AI startups unlocking enterprise value by embedding themselves deeper into enterprise workflows. If you would like to share your thoughts, hit up Anish or Eric on the community Slack or reach out via email at eric@gaicollective.com for a feature in our next newsletter!
Events Recap
A huge thanks to everyone who attended and contributed to the vibrant conversation during the Tech Talks meetup in collaboration with the MLOps Community and Microsoft Reactor! Our speakers were the stars of the evening, delivering 8+ insightful talks on lessons learned from building GenAI systems in 2023. We also had a series of themed discussion groups on open source LLMs, fine tuning / RAG, productionization, agents, and future trends! 🤩
Marin’s first AI event ever - a resounding success! Head of Community Matt Huang and GenAI Collective Member Chris Guest threw an incredible mixer at the Pond Farm Brewery in Marin. We had operators, researchers, founders, investors, enthusiasts - and most importantly, craft beers and bites. 🍻
This was the event the Marin tech enthusiasts were waiting for - and there is so much latent demand in the North Bay waiting to be activated. Many more Marin events to come! 🚀
About Anish Chadalavada
Anish is the co-founder and COO of Gradial, an applied AI company building next-gen content management solutions for creative teams. He previously led Seed / Series A deep tech investments at Point72 Ventures and cloud and AI corporate strategy at Microsoft. Anish is passionate about ensuring that AI is used to augment human potential and enabling everyone to realize their creative vision. Outside work, you can find him at live EDM concerts or PNW breweries, hiking in the Olympics, or skiing well-groomed blues! ⛷️