The AI ​​elephant in the room: Production deployments are…

Talk to any company and they will tell you they are excited about the increased productivity and returns that AI adoption could bring.

But if you dig a little deeper, you’ll find that companies are more reluctant than you might have thought at this point. From ChatGPT bans to apps failing in pre-production, there is still a long way to go before this technology becomes mainstream in production. writes Juliet Bailin, partner, General catalyst.

Accelerated adoption vs. sustainable adoption

The dominant narrative around AI is one of hypergrowth and accelerated adoption, surpass anything this has happened before.

Apple recently admitted as much when announcing its partnership with OpenAI to bring its Siri technology up to par. However, actions speak louder than words and companies still seem far from putting their enthusiasm at the service of production. Hesitancy to adopt AI among businesses is widespread: a survey in April found that a third of companies are abandoning Gen AI projects due to concerns about consumer trust, while more than one in four companies have banned the technology in their workplace due to data issues, according to Cisco.

Another investigation suggests that only 42% of companies at the enterprise level have actively deployed AI in their business and 40% say they are stuck in the experimentation phase due to the difficulty of implementation, as well as concerns about data privacy (57%) and trust and transparency (43%).

CTOs and business leaders told us how they were testing GenAI, but they were also uncomfortable trusting LLMs with their most valuable data. Over a year ago, one multinational bank we spoke with received nearly 1,000 ideas from employees on how to leverage AI in their business; zero is in production today.

While leadership teams are demanding the adoption of AI, many do not understand the value the technology could bring, or whether that value is worth the cost of deploying it. AI founders need to develop much greater trust with the companies they want to partner with if they want to create a sustainable solution.

Six ways AI startups can convince business buyers:

1. Ask what their top priorities are, not their AI goals: Most companies don’t have an overall strategy around AI; solve problems directly related to key business indicators.
2. Build trust: prioritize security, transparency, and proactively address concerns.
3. Start internally: Implement AI in non-customer-facing products first to build trust.
4. Prove ROI: Demonstrate the value of AI early and often with measurable results.
5. Prioritize scalability: Develop adaptable solutions that integrate easily and grow with the business.
6. Educate and Empower: Host workshops to demystify AI and drive adoption.

AI will bring huge benefits to businesses, but founders and teams must bridge the gap between the hype around AI and its current capabilities for businesses to feel confident in their investment.

Right now, everyone is talking about AI, but few are actually using it. If we want to overcome business hesitation, startups need to build trust and create practical solutions to convince these essential buyers. Only then will transformational AI technology evolve into sustainable businesses.