With the high complexity of artificial intelligence, it is unrealistic to expect every business leader to be an AI expert. A common element among AI pacesetters is having a corporate-wide strategy for AI. Typically, these companies have teams that oversee the AI strategy that partners with each department to create roadmaps, prioritize investments, and share best practices to leverage learnings from one group to benefit the entire enterprise.
I recently conducted a survey to understand how companies are approaching the development of AI strategy. The survey asked respondents about their companies' approaches to developing strategies for the use of AI and generative AI.
Overall, 41 percent of Technology Services Industry Association (TSIA) members, all B2B technology firms, say they have corporate teams creating strategies for the entire enterprise. The pacesetters I have found with higher adoption of AI, a wider range of use cases in production, and documented business results for AI investments tend to have corporate strategies and/or teams driving AI roadmaps at an enterprise level.
There are several advantages to this approach, including the following:
- Identifying opportunities for AI across the enterprise and pursuing technologies that can be leveraged in multiple departments, minimizing overall number of projects and tools.
- Partnering with individual departments to build a roadmap for AI investments, the strategy team provides the expertise on AI and recommendations for streamlining and automating processes, while relying on the department to be the subject matter expert for their business.
- For business leaders who have been in their role for years or decades, asking them to transform their own departments can be difficult, with more change management challenges. Having a corporate team driving transformation can push department heads to go beyond their comfort zones, accelerating transformation and also bringing in a fresh perspective to avoid the" but we've always done it that way" trap.
More than a third of respondents, 36 percent, say it is up to each department to develop their own strategies. Some companies have voiced that having a department level approach allows them to build a business case for budget, while having a corporate team driving AI projects and priorities might mean that some departments, such as service organizations, can take a back seat to sales, marketing, and product. The challenge with department-level thinking is that multiple organizations might be shopping for similar technology and duplicating efforts and not benefiting from lessons learned and best practices identified by other departments.
Eighteen percent of survey respondents say they have no formal policy, with a lot of conflicting owners and strategies. Another recent TSIA Quick Poll found that 40 percent of companies had more than six AI pilots going on in their companies and another 19 percent said it was hard to know how many AI pilots were happening. Without an enterprise AI strategy or roadmap, individual departments or business leaders can create an overload for their IT organizations in supporting pilots, ultimately impacting the success of individual projects.
Another question from the first survey asked respondents about the importance of AI/generative AI in transforming to digital sales and services and profitable XaaS business models.
More than half of companies, 55 percent, say that AI/generative AI are core to the success of department and/or enterprise transformation. Forty-one percent said that AI is important but not a driving factor in transformation. Only 4 percent said that AI/generative AI were not a top priority. No companies said they were not interested in AI at this time.
Further analysis showed that approaches to AI strategy differ by how companies see the importance of AI to transformation. Findings include the following:
- Of the companies that said AI/generative AI are core to the success of department and/or enterprise transformation, 47 percent have corporate AI strategy teams.
- This drops to 38 percent for companies that say AI/generative AI are important but they don't see it as the driving factor in transformation success.
- Of the companies that say AI/generative AI are not a top priority, only 33 percent have corporate strategy teams for AI.
Asking departments to transform themselves is difficult. While each group understands their data and processes intimately and likely knows of areas needing streamlining and automation, an outside perspective is helpful. Having centralized corporate teams driving AI strategy offers the following advantages over asking individual departments to develop their own strategies:
- Alignment with overall business goals. A corporate AI team can ensure that all AI initiatives are aligned with the company's overarching strategic objectives. This prevents the development of isolated projects that might not contribute to the company's long-term success.
- Resource optimization. A centralized team can efficiently allocate resources, such as talent and budget, to the most promising AI projects. This helps avoid duplication of efforts and ensures that the company's AI investments yield the maximum return. The downside to this approach is that departments viewed as less strategic might never be first in line for funding.
- Standardization and knowledge sharing. A corporate AI team can establish standards, guidelines, and best practices for AI development and deployment and foster collaboration and knowledge sharing among departments. This will accelerate the realization of an AI roadmap by sharing lessons learned across the enterprise.
John Ragsdale is a distinguished researcher and vice president of technology ecosystems at the Technology Services Industry Association (TSIA).