Companies to prioritize AI projects with strong business case and quick returns

Companies to prioritize AI projects with strong business case and quick returns

A round-up of some of the latest – and what to look forward to – from the world of technology

Artificial intelligence (AI) start-up investors are shifting their focus to accounting software, a traditionally subdued corner of business technology, as companies are getting prepared for a potential economic slowdown. Many investors are betting that inflation, huge interest rates, and recession distress will prompt companies to redouble efforts to track and control spending, increasing demand for AI tools. At the same time, investors say, many businesses are expected to hit a pause on spending in areas of IT with no instant impact on the bottom line.

According to a Wall Street Journal report, discretionary spending such as proof-of-concept tests—which validate whether an emerging technology is ready for commercialization—could get pushed back, but businesses see more value than ever in tech that will enhance the customer experience and give them an edge in an increasingly tight market, executives and analysts said. Companies will spend on projects that have strong business value and continue to invest in digital transformations that have a robust business case.

Cybersecurity investments to stay firm

Cybersecurity continues to evoke interest and investments in a downturn. Forecasts of a years-long economic downturn aren’t stopping cybersecurity investment funds from pouring money into both early- and late-stage security startups — at least for now. Investors anticipate that market demand for new cybersecurity products will continue into a possible recession — justifying continued investor interest in cybersecurity.

More than half of cybersecurity professionals said in an ISACA survey earlier this year that they anticipate their companies’ cyber budgets to increase in the next year. The biggest cyber investment opportunities lie in cloud security, software-as-a-service and artificial intelligence tools.

Digital transformation has changed how companies perform remote work, service customers, and deliver new products. The impetus for digital transformation has pushed organisations to adopt cloud technologies at a rapid pace. It is no surprise then, that Gartner included cloud-native platforms in its annual Top Strategic Technology Trends report for 2022, calling it a critical technology for organisations looking to gain the agility required to succeed in today’s fast-paced market.

VC funding for AI, ML projects decline

Meanwhile, venture capital (VC) funding slid more deeply in AI and Machine Learning (ML) than in software overall in Q2, falling 27.8% quarter-over-quarter (QoQ) compared to 21.6% for IT more generally. Both deal value and deal count fell to their lowest levels since Q4 2020, also lagging the rest of IT.

Of the 70 product categories tracked by Gartner, only 21 are on pace to grow in VC funding in 2022, driven by leading vertical applications including sales and marketing, information security, and drug discovery, per the Pitchbook Emerging Technology analysis.

Horizontal platform investment is lagging, as outsized revenue projections face market realities, with AI-as-a-service (AIaaS) investment on pace to decrease 87.7% in 2022. Numerous AI platform companies have struggled to reach revenue forecasts in the current financial environment, creating a greater emphasis on vertical applications that can rapidly deliver value.

High-growth use cases include accounting automation, wealth management, metaverse, and quantum AI. Use cases that both address long-term opportunities and near-term financial pressures are outperforming. VC exits continued their Q1 slowdown, maintaining flat deal value at $14.7 billion yet falling 21.8% in deal count to 100 exits.

SPAC mergers continued to close in Q2 with Pagaya, Eve, and SoundHound completing exits valuing the companies at multi-billion-dollar valuations. Several acquisitions announced early in the market downturn closed during Q2, including Snowflake’s $800 million acquisition of Streamlit and Software AG’s $584 million acquisition of Streamsets.

The Mega Exits

The closing of mega-exits demonstrates the sustained value of advanced data analytics software to database management incumbents even during economic volatility. AI leaders remained minimally active in M&A with IBM acquiring database management startup Databand for $150 million and Meta acquiring clothing size recommendation startup Presize.AI.

Emerging opportunities

Companies like DataRobot present exciting opportunities. DataRobot’s Enterprise AI platform offers end-to-end automated machine learning (autoML) tooling, including data preparation, model development, security, and monitoring. The platform is designed for data scientists, software developers, operations teams, business line users, and executives. The platform can train and deploy models across cloud, on-premises, and hybrid production environments.

Recent acquisitions in autoML (Zeff), model management (ParallelM), data visualisation (Zepl),

and data preparation (Paxata and Zeff) have been successfully integrated to create a data science platform that can compete with hyperscalers. In Q3 2021, the company acquired machine learning operations (MLOps) startup Algorithmia and predictive analytics startup Decision.AI. Algorithmia was achieving a leading market position in MLOps after receiving investment from Google and Microsoft, making the acquisition highly strategic for DataRobot. The acquisition of Decision.AI shows the company’s strategy to move downstream to the application layer and make its platform user-friendly for a wide range of business users. The company is likely to continue to focus on the application layer going forward.

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