Business Strategy for AI May Include Hiring a Chief AI Officer
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Business Strategy for AI May Include Hiring a Chief AI Officer
Having a business strategy for incorporating AI will help the enterprise to move more quickly and be more likely to be successful; where to start is a challenge
By John P. Desmond, Editor, AI in Business
More than 50 percent of companies don’t yet have a business strategy for incorporating generative AI.
That’s the finding of a study from Forrester Consulting that was commissioned by Grammarly, the provider of cloud-based writing assistance services. Entitled “Maximizing Business Potential with Generative AI: The Path to Transformation,” the report finds that companies see the business benefits of generative AI, but are taking a haphazard approach to addressing it that could put them at a competitive disadvantage.
The report found companies are using generative AI for the following purposes: improve writing quality (47 percent); increase revenue (46 percent);l speed up execution (42 percent), and innovate more quickly (43 percent). Only 45 percent reported having an enterprise-wide strategy to ensure AI deployment is aligned across the organization.
“If you’re a business leader, adopting generative AI is not optional—your teams and competitors already are,” stated Matt Rosenberg, Grammarly’s Chief Revenue Officer and Head of Grammarly Business. “Those who fail to recognize or underestimate the value of the technology will fall behind, but businesses need to know how to operationalize it at scale. Carefully executing a company-wide strategy with holistic solutions is essential to achieve transformation through generative AI—and avoid long-term risks.”
The report is based on a survey of 301 technology decision-makers in North America and the UK. Among the findings also: some 74 percent of companies using generative AI reported it is saving workers the equivalent of 2.5 hours each day, or 13 hours each workweek.
Where to Start On an a Transformative AI Strategy
Another observer and participant sees that AI is the next wave of truly transformative technology, “the defining technology of our time, changing the way we live and work.”
“Right now every company, no matter the size or industry, should be thinking about AI,” stated Christopher Young, executive vice president, business development, strategy and ventures at Microsoft, in a recent account he authored in Harvard Business Review
.Maybe it’s a self-serving comment, since Microsoft, like tech behemoths Google and Amazon, has a huge business arm providing services to help customers adopt AI in their businesses. And it’s true. To not be thinking about how to implement AI in business is pretty much career and business suicide today. It’s a defensive and offensive strategy.
Where to start is a good question. “The best way to learn about AI is to use it,” Young suggested. “Try applying it to whatever task is in front of you and see what it’s good at and what it’s not.”
He used Bing and ChatGPT to help provide ideas for a speech. He has used Microsoft 365 Copilot, offering AI integration across Microsoft apps to help produce slides, summarize documents and recap email exchanges.
Developers are certainly tapping into generative AI, especially users of tools via GitHub, which Microsoft acquired in October 2018. The GitHub Copilot today is used by more than one million developers, has generated over three billion accepted lines of code and is said to be the world’s most widely-adopted AI developer tool, according to an account on the GitHub blog.
To find potential use cases, look for repeatable, rules-based processes that can be streamlined with AI, Young suggests.
Microsoft clients using AI strategically include PwC, using Azure OpenAI Service to expand and scale its own AI offerings while also helping clients in industries including insurance or healthcare; and CarMax, using AI to analyze customer reviews to surface key takeaways for buyers about every make and model in its inventory.
“Leaders who embrace AI now and take action to understand it, experiment with it, and envision how it can solve hard problems are going to run companies that thrive in an AI world,” Young stated.
Organizing for AI: The Chief AI Officer
Once a company decides to exploit the AI opportunity, it’s not enough to hire a group of machine learning scientists and data analysts, if they can be found. How best to organize the company to incorporate an AI strategy will be critical to success. To better execute, some firms have appointed a chief AI officer.
“Rather than being applied to isolated use cases as an afterthought, AI must be built into the strategic direction of any company and must be considered a fundamental part of the road map; which necessitates the hiring of a chief AI officer (CAIO),” stated Dylan Fox, founder and CEO of AssemblyAI, offering tools to build AI applications with voice data, in an account he authored in a recent issue of Fast Company.
The CAIO should report to the CEO and be a member of the executive leadership team.
Each CAIO will need to focus the effort on what works best for the company, such as personalizing in retail, higher automation in manufacturing or fraud detection in financial services. From the top-down perch, the executive is in a good position to identify opportunities for growth and innovation that rely on the power of AI. Overseeing change from the top down can make things happen at a speed to keep the company competitive. And the CAIO is in a good position to oversee and to judge whether the AI is being used in an ethical and responsible way.
The strategy needs to ripple through all parts of the company. “The CAIO should work closely with product, marketing, finance, and operations to identify areas where AI can be used to improve efficiency and drive growth across the operating plane,” Fox stated.
Good luck finding CAIO candidates, by the way. The ideal candidate would have a strong background in AI, a deep understanding of the company’s industry, and experience overseeing large, diverse teams and working in a fast-paced, dynamic environment.
It’s likely to take time for a new CAIO to assimilate into the company culture. “It will be initially more ambiguous than other leadership roles,” Fox advises.
Questions to Consider While Strategizing
CIOs considering generative AI within an AI strategy could benefit from assessing the readiness of the business before proceeding, suggest the authors of a recent account in InsideBigData. Key considerations include:
Being honest about the enterprise’s level of AI maturity, to help with the correct positioning.
Assess the current state of the organization’s AI infrastructure, such as whether the current pipelines accommodate generative AI tools. This suggestion, “Addresses the most pressing questions at the board level, like the profitability of chasing a trend and ROI,” stated Sreekanth Menon, VP and Global AI/ML Services leader for Genpact, who consulted on the InsideBigData account.
Map the current workforce skill levels with the competencies needed to support generative AI. Identify initiatives and incentives for the current workforce to upskill to meet the demand. With the generative AI market in its infancy, these skill sets are unlikely to be found by hiring.
Consider what it’s going to cost for the transformation of people, processes and technology. “This helps establish an environment of sanity,” Menon stated.
Ask the top customers about their attitude and sentiments towards generative AI. “This will help the organization calibrate its strategies for profitable outcomes,” he suggested.
Identify the risks of using generative AI, such as hallucinations and prompt injection attacks, which can achieve unauthorized access or manipulate responses. The privacy and data security implications of generative AI must also be considered, especially in healthcare, financial services and other regulated industries.
A company’s AI governance practices become relevant. These can vary by geography, with more state and national regulations coming forward.
It’s nice to have a responsible AI framework, to mitigate the risk of using AI. “With gen AI still in its infancy, the risk taxonomy will evolve. So, CIOs should consider what changes are required to the existing RAI frameworks to make gen AI usage safer,” Memon advised.
Read the source articles and information in a report from Forrester Consulting, in Harvard Business Review, in Fast Company and in InsideBigData.
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