Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

Menlo Ventures’ State of Generative AI in the Enterprise Reveals New Data on Sentiment and Adoption Rates, Highlighting Opportunities for Startups

Menlo Ventures, a leading venture capital firm heavily invested in AI technologies, released The State of Generative AI in the Enterprise, a flagship report based on a survey of 450+ enterprise executives that details current generative AI adoption and, based on that data, makes projections for where the next wave of AI innovation will happen.

According to the report, enterprise investment in generative AI remains surprisingly small, totaling $2.5 billion this year–significantly less than the $70 billion invested in traditional AI and the $400 billion spent on cloud software. At the same time, the data shows that the number of enterprises using AI increased 7% in 2023, with AI spend growing by 8% and eating into total enterprise tech spend, which only grew by 5%.

Recommended AI News: Riding on the Generative AI Hype, CDP Needs a New Definition in 2024

AIThority Predictions Series 2024 banner

The majority of this spend goes to incumbents. The report explains how “Big Tech” companies and category leaders were able to swiftly mobilize and capture a significant portion of the market, leveraging advantages in brand, scale, budget, and engineering resources to integrate AI capabilities into established products. As a result, the market share held by incumbents is currently estimated to be $1.2 billion1, leaving little room for challengers to gain traction.

“Given the level of hype in the market, a lot of people will be surprised to see that enterprises are still in the early innings of investing in generative AI,” said Naomi Pilosof Ionita, Partner at Menlo Ventures. “Enterprises are still in ‘experimentation mode’ and buyers cite ‘unproven ROI’ as the main barrier to AI adoption.”

Related Posts
1 of 41,052

To unlock the enterprise market, AI solutions must upend the status quo by demonstrating significant gains in productivity, replacing old methodologies, and rewriting workflows in ways that feel entirely new and radically different. “It’s not easy for startups to compete in a market that favors established players. But where startups have an advantage is in their ability to blaze new trails in areas that incumbents may initially disregard or dismiss, and their willingness to go after markets so new that they’re anybody’s game,” said Derek Xiao, an investor at Menlo Ventures and co-author of the report.

Recommended AI News: NVIDIA Supercharges Hopper, the World’s Leading AI Computing Platform

The report identifies three areas that offer enormous potential for startups to break out:

  • Vertical AI: Research shows that the marketing and legal industries currently lead the way in vertical generative AI adoption. In industry-specific applications, AI will reinvent human-machine collaboration, becoming the driver for end-to-end automation rather than merely a copilot or collaboration platform.
  • Horizontal AI: Horizontal solutions are popular because they can be used across industries and departments, increasing workflow efficiency beyond what was previously possible. As AI becomes more capable of reasoning, collaborating, communicating, learning, and predicting, next-generation workflow tools will not only allow machines to augment or automate routine tasks, but—with advanced approaches like agents and multi-step reasoning—take on work that only humans could do before.
  • The modern AI stack: New generative capabilities require new tools for building LLM apps, including databases, serving infrastructure, data orchestration, and pipelines. Although still a “work in progress,” the modern AI stack attracts the largest percentage of enterprise AI investment, making it the biggest new market in the generative AI domain and an attractive focus for startups.

Recommended AI News: XConn Technologies Announces Partnership with Liqid

“AI represents a massive opportunity, and I’m particularly excited about the AI stack. In the last few months, components of the stack have accelerated quickly, going from experimentation and construction to stabilization and standardization, but it’s by no means complete yet,” said Tim Tully, Partner at Menlo Ventures. “Looking ahead, new building blocks in the stack – from model deployment and inference to data transformation to observability and security – will continue to emerge, creating an incredible opportunity for startups building for the modern AI stack.”

[To share your insights with us, please write to sghosh@martechseries.com]

Comments are closed.