In a recent survey of over 570 executives by Bain & Company, 75% stated that AI has already met or exceeded their expectations. According to the firm's fourth annual Global Technology Report 2023, the current generation of AI tools and models could help companies speed up 20% of worker tasks without loss in quality.
While the ease of access to large language model (LLM) application programming interfaces (APIs) has made it relatively easy to demonstrate new AI-powered products, Bain’s survey revealed that 89% of software companies are already using AI to differentiate their products, which is 15 percentage points higher than other sectors.
It added that early adopters of AI are already seeing results and productivity gains as they explore new ways to use AI for their businesses.
“Innovation is happening quickly, and we are still in early days,” said David Crawford (pic), global head of Bain’s Technology practice. He added, “Three out of four software companies we surveyed believe that early movers will maintain a sustained advantage that will not level off.”
Software leaders anticipate significant opportunities for AI to drive top-line growth and enhance customer retention. Our research indicates that in this dynamic environment, companies are adopting a wait-and-see approach regarding AI risk falling behind.,” Crawford said.
The report suggests that software companies must consider the implication of their customers and competitors adopting generative AI, which can have an impact on their core business.
It notes that customer concerns related to data protection and access, personally identifiable information, audit trails, prompt grounding with proprietary data, and integration with other machine learning (ML) and automation technologies are typically addressed at the platformlevel, beyond the LLM.
The report emphasised that this is an opportunity for software companies to differentiate themselves by leveraging established positions within customer architectures.
Generative AI talent implications
As customers integrate AI into their own processes, job roles are expected to undergo transformation. According to the report, functions such as engineering, sales and marketing are poised to benefit from AI in the next 18 months. Companies will require additional engineering talent skilled in AI and ML, particularly those with experience in building or integrating LLMs.
The report also highlights that generative AI will revolutionise how companies market and sell their products and services, as it enables significant automation throughout the entire customer lifecycle. This includes areas like demand and lead generation, digital self-service sales, customer success, and other support activities, all of which can benefit from the automation capabilities of generative AI.
When it comes to investor appetite, Bain’s report reveals that most investors believe that AI will have a significant effect on the tech sector. In fact, investors’ enthusiasm for AI is high, with AI and ML investments leading venture growth in the first half of 2023. However, most investors think that the evolution of the competitive landscape remains to be seen.
Therefore, to mitigate disruption risks, investors must consider both disruption potential and structural barriers in the market. They should also consider whether or not companies own proprietary data could enrich generative AI applications.
“Leading funds are not waiting to see how generative AI changes this space. They are taking proactive steps toward capitalising on the potential of their incumbent software assets,” noted Crawford.
Investor perspectives: A buyers’ market is coming for tech assets
The report underscores that investor sentiment in the broader tech sector has been lackluster since the third quarter of 2022. With deal volumes and exit values decreased, a growing backlog of deals, including more than US$700 billion (RM3.2 trillion) of tech assets purchased between 2018 and 2021, has led to longer hold times of tech portfolio companies.
In 2023, nearly half of tech portfolio companies were held for more than four years. This backlog of long-held portfolio assets is growing faster than the record level of dry powder that remains available, setting the stage for a buyer's market when activity picks up.
Bain notes that investors evaluate tech companies differently depending on a company’s context and point in the life cycle. Some investors are drawn to young, disruptive companies based on their growth potential. As companies and their markets mature, investors expect a mix of growth and returns. Mature companies with a proven track record in stable markets can expect slower growth while their investors are closely focused on profitability.
To maximise value, investor relations strategies of tech companies should change over time as markets mature. Understanding the role between market maturity, investor expectations, and sources of total shareholder returns are essential to delivering shareholder value at every stage of the journey.
Post-globalisation: Tech manufacturers diversify supply chains and R&D locations
In another chapter of the tech report, Bain predicts that the global footprint of the technology value chain is likely to look very different, a decade from now. Macroeconomic shocks in the last few years have prompted tech manufacturers to build resilience into their supply chains, primarily by expanding their geographic footprints to new locations in Asia, Europe, and North America, creating more flexibility within their talent pools.
Anne Hoecker, leader of the firm's Americas Technology practice, noted, "The initial response led companies to first reconfigure their supply chains. Now, they are extending these efforts to encompass R&D, talent, and innovation centers."
“The key is practical resilience which means diversifying the most critical aspects of your business while getting closer to end markets,” she added.
Hoecker emphasised that it will take time for companies to move production, and they will also need to balance the risk of oversupply as new sites come online. “The semiconductor industry is incentivising the build-out of new fabs outside of historical locations, primarily targeted at newer chips at smaller node geometries, but new fabs take three to five years to come online and produce chips in volume. “
She also pointed out that even downstream original equipment manufacturers and component suppliers that are moving production to new locations will require a few years to materialise and deliver the same standards as original factories.
Other topics discussed in this year’s report include AI and cybersecurity, digital innovation, and intelligent edge. The full report can be accessed here.
