A decade ago, artificial intelligence (AI) was primarily planted in the realm of large enterprises with large budgets, a core competency in AI and teams of data scientists. Today, that has changed dramatically. AI is now embedded in more technology platforms, with more out-of-the-box capabilities available. With off-the-shelf AI tools,, implemented by professional services consultants with AI expertise, an internal team of data scientists is no longer required.
At the recent TSIA World INTERACT conference, 32 of the 34 exhibiting sponsors demonstrated AI and generative AI capabilities. Many of these sponsors target small and midsized businesses, verifying that AI is no longer out of reach for smaller firms.
I recently conducted a TSIA Quick Poll survey to better understand the importance of AI in technology evaluations. The quick poll asked, "When considering purchasing new technology, how important are the AI/genAI elements of the solution?" Two versions of the survey were implemented, one targeting technology buyers (TSIA members, primarily B2B technology companies), and the other targeting technology sellers (TSIA partners). The quick poll results, with data representing both TSIA members and TSIA partners, can be seen in Figure 1.
Figure 1
Importance of AI and Generative AI When Purchasing New Technology
Source: TSIA Quick Poll: Roadblocks and Obstacles to AI Success.
Of TSIA members, the largest percent, 44 percent, said that AI/genAI are a critical part of technology evaluations. Only 5 percent said they are not evaluating AI as part of product selection.
Another question asked, "How important do you see AI/genAI in transforming to digital sales and service and profitable XaaS business models?" Of the companies that claimed that AI/genAI are core to the success of their departments and/or enterprise transformations, 65 percent admitted that vendors won't be considered without compelling AI stories or that AI is a critical part of technology evaluations. Among other companies that claimed AI/genAI are important but not the driving factor in transformation success, only 35 percent admitted that vendors won't be considered without compelling AI stories and that AI is a critical part of technology evaluations.
However, the perspective of technology sellers is a bit different. Of those surveyed, 23 percent claimed that if vendors don't have compelling AI stories, they won't be considered. This indicates that AI is becoming a driving factor in sales cycles.
With most technology vendors offering AI elements and roadmaps of additional planned AI/genAI features, companies shopping for technology should understand the potential each incumbent vendor offers, how it could impact their departments or enterprise AI strategies, and factor this into their AI roadmaps. Ask vendors for references for any AI capabilities you see as critical to ensure the features are being adopted and are delivering the anticipated value.
The quick poll also asked respondents to rate multiple factors as potential obstacles on a scale of one (low) to five (high). The results can be seen in Figure 2.
Figure 2
Average Ranking of Obstacles to AI Progress
Source: TSIA Quick Poll: Roadblocks and Obstacles to AI Success
Overall, technology buyers said the major obstacle to the selection, purchase, and implementation of AI/genAI technologies is budget, equating to an average roadblock/obstacle rating of 3.8 on a 5-point scale.
From a technology seller perspective, oversight/involvement of IT and lack of vision/strategy/roadmap for AI are the major obstacles, equating to an average roadblock/obstacle rating of 3.8. This roadblock/obstacle factor came in second place with technology buyers, equating to an average score of 3.5.
Change management/culture, such as fear of AI taking jobs, was only rated a 3.4 by technology buyers. This indicates companies and employees are becoming less apprehensive about AI and are starting to shift away from the sentiment that AI would eliminate jobs, a common thought in the early AI hype cycle.
Below are additional findings regarding roadblocks and obstacles to the selection, purchase, and implementation of AI.
- Not surprisingly, budget is a major obstacle for companies that say AI is not a top priority, with an average score of 4.0, compared to an average of 3.8.
- Companies that have corporate teams creating enterprise AI strategies seem to struggle less with vision/strategy/roadmap, rating this obstacle as 3.3, compared to an average score of 3.5.
- Companies that claim to have many conflicting owners and strategies for AI rate lack of vision/strategy/roadmap as a 4.1, flagging it as a higher concern than the average score of 3.5.
Securing budget is challenging, with limited corporate funds and multiple departments vying for the same funding. During the evaluation process for new technology, companies should ask vendors to provide case studies. Creating a realistic roadmap for the anticipated return on investment (ROI) for an AI project can help in boosting the priority of your project and securing funding.
AI/genAI can be a game-changer that can boost productivity, improve the customer experience, and create insights that can generate additional revenue. Nonetheless, few companies have become masters of AI, and many roadblocks and obstacles remain. To ensure the successful creation and execution of an AI strategy, I recommend the following:
- According to the quick poll survey results, trust in AI is important to company transformation and how companies factor this importance determines their approach in developing an AI strategy. If your company does not have an enterprise strategy or corporate team driving the AI strategy or roadmap, the starting point is identifying executives who trust in AI to create insights and inform decision-making.
- For tech companies, budget is the single biggest obstacle to AI success. With so many projects on the roadmap, battling for funding and mindshare with IT can be overwhelming. The best approach to help secure funding is to build a realistic ROI model for your planned investment based on case studies and actual results customers achieve.
- Assess the existing AI capabilities of all your incumbent vendors before shopping elsewhere. If you identify net new AI features you need, which aren't provided by existing vendors, be sure to check customer references when considering new technology providers. My experience is that some vendors are messaging capabilities that may still be on the roadmap which increases the risk of a purchase.
John Ragsdale is a distinguished researcher and vice president of technology ecosystems at the Technology Services Industry Association (TSIA).