More than a decade ago, Nicholas Carr,in his workDoes IT Matter, suggested that the widespread availability and low prices of technology made it more of a utility like electricity or water, versus a competitive differentiator. This may be happening with artificial intelligence to some degree.
It appears that AIs early adopter phase is ending; the market is now moving into the early majority chapter of this maturing set of technologies, write Beena Ammanath, David Jarvis and Susanne Hupfer, all with Deloitte, in their most recent analysis of the enterprise AI space. Early-mover advantage may fade soon. As adoption becomes ubiquitous, AI-powered organizations may have to work harder to maintain an edge over their industry peers.
Seventy-four prevent of 2,727 executives responding to a Deloitte survey agree that AI will be integrated into all of their enterprise applications within three years. Although adopters are still bullish on AI, their advantage may wane as barriers to adoption fall and usage grows, Ammanath and her co-authors state. Organizations are finding it easier and easier to employ AI technologies. Data science and machine learning platforms have proliferated; AI-optimized hardware is providing greater compute power. It is now easier to train algorithms through self-service data preparation tools, synthetic data, small data, and pretrained models.
It is increasingly clear that we are on the path toward an era of pervasive AI, they add. The challenge now is leveraging AI in innovative ways to maintain its advantages, the study finds. For example, much of the work with AI is still confined to managing IT systems. In addition, there still isnt enough AI talent to go around.
At least 26% of the companies surveyed can be considered seasoned AI adopters, meaning they have undertaken a large number of AI production deployments and have developed a high level of AI expertise across the board. These AI leaders are still seeing competitive advantage 45% of this group said that AI technologies have enabled them to establish a significant lead over their competitors, versus 26% of the entire sample.
Still, this means a majority of even the most advanced AI companies, 55%, still arent seeing competitive advantage. Part of this may be due to the fact that AI is still confined to IT departments and functions, including cybersecurity Forty-seven percent of respondents indicated that IT was one of the top two functions for which AI was primarily used, the survey shows.
This could mean that companies are using AI for IT-related applications such as analyzing IT infrastructure for anomalies, automating repetitive maintenance tasks, or guiding the work of technical support teams, Ammanath and her co-authors note. Tellingly, business functions such as marketing, human resources, legal, and procurement ranked at the bottom of the list of AI-driven functions.
An area that needs work is finding or preparing individuals to work with AI systems. Fewer than half of executives (45%) say they have a high level of skill around integrating AI technology into their existing IT environments, the survey shows. This could include data science and machine learning platforms, enterprise applications powered by AI, tools for developing conversation interfaces, and low-code or no-code tools. Across all these different technology areas, 93% are using cloud-based AI capabilities, while 78% employ open-source AI capabilities.
Ammanath and her team offer some suggestions for keeping the edge with AI:
Pursue creative approaches. Take inspiration from inventive use cases to develop solutions that are both useful and novel.
Push boundaries. Expand your view of what may be possible to accomplish with AI technologies. Try to pursue a more diverse portfolio of projects that could potentially enhance multiple business functions across the enterprise.
Create the new. Look to develop new AI-powered products and services that take advantage of the technologies ability to learn and solve problems that humans cant.
Expand the circle. Move AI beyond the IT department by involving more of the business in AI efforts. Look for new vendors, partnerships, data sources, tools, and techniques to advance your efforts.
Leverage a diverse team. Include both technical and business experts in selecting AI technologies and suppliers. Having a broad perspective from developers, integrators, end users, and business owners can help ensure organizational alignment and a focus on business outcomes. Along with any vendor support consider using working groups, dedicated leaders, or communities of practice.
Actively address risks. Developing a set of principles and processes to actively manage the range of AI risks can help build trust within your business and with customers and partners.
Challenge vendors. While it is important to build trust and transparency with providers of your AI-powered systems, it can be equally essential to ensure that what they provide is aligned with your organizations ethical principles.
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