90% VC-Backed Companies Launching AI Tools: What You Need To Know

Today, Productboard, the customer-centric product management platform, released a new AI and R&D survey examining how the AI boom, layoffs, economic turmoil and more are impacting product and engineering teams and company investments in product development.

Generative AI into the Spotlight

When ChatGPT reached 1 million users in only five days, it thrust generative AI into the spotlight, and the hype has only grown since then. There has been a lot of demand on software and internet firms to develop and provide generative AI capabilities or include Chat GPT in their products, and even conventional businesses are thinking about how they may utilize it to boost productivity.

 “Genius is 1% inspiration and 99% perspiration.”- Thomas Edison

Productboard wanted to investigate how the product and engineering teams were impacted given the unstable state of the economy, layoffs, the rise of AI, and other factors. Today’s release of our latest poll on AI and R&D does precisely that. More than 300 CEOs, Founders, Chief Product and Technology Officers, and VPs of Products from startups to publicly traded organizations provided their opinions in the poll. This year’s poll, which was conducted between the middle of April and the middle of May, included participants from the portfolio businesses of renowned venture capital firms such as Bessemer, Dragoneer, and Kleiner Perkins, as well as users of Productboard and Tomasz Tunguz’s online newsletter. Software and technology accounted for 70% of responses, with the remaining respondents hailing from a variety of sectors, including finance, healthcare, manufacturing, education, and retail.

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The results of AI and R&D survey

• 90% of businesses have employees working on generative AI in their products, and 64% want to release them before the end of the year.
• With startups assigning 1-2, medium allocating under 5, and the majority of big enterprises allocating under 10 team members, the majority of businesses are allocating tiny teams in relation to their size.
• Over 80% of businesses aim to spend the same amount or more on R&D, with over 50% planning to raise total investment in R&D, while over 30% of businesses plan to reduce overall spending this year.
• R&D personnel was reduced less than that of other departments in corporations that made layoffs this year.
• Businesses now place a higher priority on innovation than on spending on core goods and technical debt.
• Our survey shows that a third of startups and almost half of bigger enterprises have reduced their total spending this year.
• However, 82% of businesses with over $10M in annual sales want to boost or maintain their R&D spending; for early-stage startups, this percentage rises to 95%.
• In 2023, more than 28% of the businesses polled reported layoffs. R&D teams were laid off substantially less often than other departments among those who made layoffs.

Nearly everyone has set aside some personnel to support generative AI

• Almost all (90%) of organizations are assigning engineers and product people to integrate generative AI to their products, according to our poll, which was largely conducted among numerous respondents with connections to the VC industry.
• The majority of early-stage startups, mid-sized organizations, and biggest corporations all allocate under two team members, under five team members, and under ten team members, respectively. However, allocations are still on the lower end compared to total team sizes.
• Nearly 30% of businesses will add additional AI specialists to their teams.
• In 54% of businesses, generative AI is being handled by current team members. Because generative AI is still so young, there may be a shortage of experienced team members.
• 10% of respondents said they had already deployed generative AI capability.
• 19% said they were releasing this quarter despite the many objectives and diversions on R&D agendas this year.
• By the end of the year, 64% will introduce functionalities.

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The AI boom, Layoffs and Economic turmoil

Know that your rivals are likely investing in generative AI if you haven’t already. There will be fierce competition for generative AI resources. In order to augment external hiring, training for your current personnel will be essential. Long-term success will depend on product strategy and agreement on which enhancements will really matter. Many could rush to get “something” out the door, but in order to really affect revenue, they must pay attention to consumer wants and use, develop strategic product strategies, coordinate efforts throughout the company, and execute well. More extensive R&D data: Many businesses are reducing spending while maintaining or boosting R&D expenditures.

The top priority for R&D is innovation.

Where is all of that money going, then? The most critical investment priority across all market groups were Innovation & Differentiation, followed by core products and technical debt. Sadly, despite having the largest allotment of resources, the majority of teams felt they lacked the resources necessary to complete their tasks this year.

What Are R&D Teams’ Sizes?

Depending on a company’s product, go-to-market strategy, industry, stage of development, target market, and other factors, the distribution of how much it spends on R&D varies considerably. Our analysis reveals the distribution below. Teams in larger organizations tend to be bigger, as expected.

However, when businesses grow generally, they tend to spend less money on products and engineering. As expenses rise in sales, marketing, and operations, companies may progressively cut down on product investment if they have a good product-market fit.

For product teams, what does this mean?

Many businesses are reducing workforce and total spending in this challenging economic climate. However, based on our study, organizations are prioritizing their product and engineering teams as a means of surviving the current economic crisis. There is more pressure than ever to produce outcomes. Given this dynamic, R&D teams have to take into account three major themes.

Drive prioritization alignmentLack of alignment is one of the main problems that businesses today are facing. Particularly when businesses grow and silos develop within the organization, priorities set by one team may not be the same for others. This may result in a functional mismatch between product components, delivery delays, and significant failure to meet expectations. Priorities may be made apparent from the top down by having a single source of truth system for product development and a transparent roadmap that unifies the organization. Improve your ability to execute – Even if you’ve aligned teams from R&D and the business and established the proper objectives, you still need to DELIVER on the goal. It takes a lot of work to get the proper individuals to agree on what has to be done when and how. Execution is often what makes the difference between mediocre and great achievement.

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Make sure you’re putting the proper product characteristics first. According to their previous market study, 64% of respondents said their releases and products weren’t always favorably accepted. It is insufficient to send items that you believe people will desire. You must BE SURE that your development efforts, particularly those using generative AI, are being directed toward the things that will have the most influence on your customers and prospects and provide the greatest return on investment.

Conclusion

In conclusion, their findings demonstrate that many businesses are making significant bets on their product and engineering teams to get them through the current economic crisis and into leadership positions on the other side. There has never been more demand on R&D to meet these standards and demonstrate genuine ROI.

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Today’s struggling economy is a major burden for a lot of companies. However, investing in superior goods, innovation, and effective execution will increase your chances of becoming the industry leader, both now and in the future.