Many of you downloaded our report last week titled Shift Happens-The Changing Business Landscape in 2024 (if you missed it, I have included a link to the report below).
One key theme we explored with C-level executives we interviewed for the report is their propensity to adopt AI in their operations in 2024 and what form it will take. In this post, I double click on those findings and their implications for those who are gearing up for selling AI based solutions. Here are key takeaways from our study:
Phase 1: The initial pattern, especially in the CIO suite, is that the vendors of solutions they use within IT and their line-of-business operations will be quick to adopt these into their product suites. Microsoft 365 Copilot was the most frequently mentioned brand name when asked to provide examples. Those using cloud providers such as AWS also expected AI to further optimize their cloud infrastructure, although no specific services were as high in recall (despite the fact that our study was fielded around the time AWS Re-Invent event had been completed). The consumer analogy to this phase provided by a C-level executive we interviewed is akin to the purchase of products containing an ingredient, say sugar-sweetener such as Stevia or Monk Fruit and the expectation that manufacturers of products they regularly purchase such as soft drinks would be expected to include these in their product lines.
Phase 2: The next AI adoption phase would be harnessing AI into their day-to-day business operations such as the manufacturing floor, facilities management and others. To this end, CMOs and Marketing leads were most proactive in early experimentation and use of AI in customer-facing communications. Starting points were often the executive themselves opening a personal account on Chat GPT "to play with". The consensus among our panel was that these LLM-based tools are about 75% accurate with the remaining 25% being inaccuracies and "hallucinations". With Chief Revenue Officers and top sales executives, AI tools are expected to play a major role in their ongoing quest for being more data driven in their customer outreach. In the full report, we discuss some challenges such as lack of skill and motivation on the part of their salespeople to use data in their outreach, most notably with "old-school" long-tenured sellers in their companies. In the consumer sugar substitute analogy, this would be akin to purchasing the sweetener in its raw form to use as an additive in place of sugar in products they consume such as cereal or yogurt.
Phase 3: The final expected adoption phase is the implementation of AI in some form or another into their respective end-products. For technology product vendors, especially SaaS companies, this phase comes much earlier and for most, is already well underway. In the full report, we discuss how SaaS companies and cloud service providers are in a race with their competitors to implement AI-features. And as indicated in Phase 1 above, customers of these companies have high expectations for the availability of well-integrated products they use in 2024. For the non-SaaS and cloud companies in our study, there are expectations that by the end of 2024, AI will show up in at least minimal form in their end products for B2B products, and in some form at least in the production of B2C and D2C offerings, such as contributing to better custom fitting of clothing for an ecommerce fashion company. The consumer sugar-alternative analogy breaks down somewhat for this use case, although the executive who first brought it up offered up the analogy of using the sugar alternative in original cooking of items such as baking cookies.
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Alan Nazarelli is Founder & CEO of Silicon Valley Research Group. Based in San Jose, CA with offices in Seattle and New York, the company works with the world’s most innovative brands to provide timely and actionable market intelligence and strategic guidance to enable them to make well-informed decisions to positively impact revenues and profits and to achieve their growth targets. Connect with Al on Linked in
Topics: Market Research Best Practice