Editorial
GenAI's ascent from obscurity to ubiquity is a modern corporate odyssey. Unbeknownst to many executives, ChatGPT’s explosion in media and use marked a turning point, showcasing the potent potential of generative AI and large language models (LLMs). Current analyst research underscores this fact: with 10% of organizations integrating AI into production and 45% in the pilot phase by Q3 of last year. The trend is clear.
However, piloting these technologies with a blueprint for success is crucial. This means being nimble yet strategic, focusing on concrete metrics for success and fostering a culture of innovation. As the discourse on this topic unfolded in a recent chat with CIOs on X, it's evident that the blueprint for success is not just about technology, but also about the human and organizational readiness to embrace and steer it.
CIOs Share Their Maturity With GenAI
The corporate landscape is at varied stages for GenAI adoption. Enthusiasm abounds as enterprises dabble with the potential for this technology. While the likes of Microsoft deploy AI at scale, tailoring next-generation tools to ChatGPT and Copilot, many others are toe-dipping and piloting programs that streamline tasks from drafting content to decoding complex contracts. The more adventurous are weaving AI into the very fabric of their operations, particularly in areas where the user needs are clear cut, and demand is evident. But caution prevails, with a wary dance around the hype, ensuring that the promise of AI doesn't overshadow its practical application.
With most CIOs exploring, many piloting and a significant chunk deploying, it's a mosaic of progress. A vanguard are already harnessing AI solutions, and the rest are leveraging off-the-shelf software, marking a technological democracy in motion.
Former BusinessWeek CIO Isaac Sacolick says, “There is clearly a lot of exploring/piloting. I am guessing 10x over production deployments or where GenAI is cemented into a workflow. Having said this, I am seeing a ton of summarization such as:
- Meeting minutesLong email threads
- Big boring docs, like contracts and SEC filings
- Content marketing
- Policy drafts”
In-transition CIO Martin Davis similarly finds, “Companies are in all sorts of stages, from playing with it, to pilot purgatory, to implementing it. Some are live with low-hanging fruit around support bots. I am seeing production deployments in the following areas:
- Copilot in software development
- Marketing workflows
- RAG where the user base and use cases are tightly defined
- Enterprise search -> enterprise prompting”
New Zealand CIO Antony McMahon, however, stresses, “We are very much at exploration mode over here. With this said, we are seeing some practical use cases but also trying not to get too caught up in the hype of which there is still a lot.”
An Effective GenAI Pilot Program
Crafting an effective GenAI pilot is akin to preparing for a long-distance run; wisdom lies in pacing, not sprinting. It's about marrying prudence with ambition — seeking out internal use cases that are ripe for transformation while skirting the tempest of trying to overhaul the entire enterprise in one go. CIOs are tailoring their approach: blending strategic opportunism with a nurture for organic growth and choosing fields of maturity or investing in them as needed.
Manhatanville CIO Jim Russell says, “There is no one size fits all. You’ll need a blend of opportunistic exploitation and organic development. Some areas have enough maturity, or you can buy maturity while others require patience.”
Assembling the GenAI puzzle requires organizations begin with an end in mind: what's the goal? CIOs should frame their actions to yield tangible results and weigh the risks and rewards. It is important to begin with bite-sized projects, manage them tightly,and guard data jealously. Don't chase data purity like a mirage. Focus instead on the data's origins, its journey and its contextual usage. Aim for meaningful outcomes — whether boosting efficiency today or seeding growth for tomorrow.
First CIO Deb Gildersleeve suggests, “GenAI is not much different from piloting other technologies. What do you want to learn and accomplish with the pilot, what tools do you need to use, who will be testing and evaluating and how will you document findings and communicate them out?”
In the laboratory of innovation with your pilot, be cautious with rigorous domains, like the thorny thickets of financial calculations. Your pilot should be significant enough to impact but nimble enough to pivot without causing an earthquake. Harness your own data, ensure it solves a concrete problem and above all, prioritize safety. As you tread this path, remember you're here to enhance tasks, not to replace the human essence of work.
To do this, Sacolick says, “Work backwards: What's the objective? How do you make your results actionable? What are the benefits and risks? Then, you can start planning the most valuable and lower-risk use cases.”
Davis agrees when he says, “CIOs should be clear on the objectives and ensure they can control the situations and measure results, and they should make sure they can secure with their key data.”
Remember, an effective GenAI pilot isn't merely about deploying technology. It is about generating tangible business transformation.
In this process, Constellation’s Research VP Dion Hinchcliffe says:
- Don’t use yet in highly rigorous domains (financial calcs)
- Pilot something big enough to matter, small enough to survive
- Find a way to use your own data
- Solve a real problem
- Be safe!
AAAS CIO Jay Brodsky argues, “It is not so much a secret, but don't forget the ethical component to any GenAI pilot. Understand the biases, be transparent, act with accountability and be very careful with the security of your data.”
Produce Outcomes to Determine Deployment
To move forward with a GenAI deployment, a captain — be it a CIO or a designated leader — must chart the course from the outset. This involves establishing clear objectives and expected outcomes. It also relies on navigating and continually updating the plan as learning occurs. Cultivating GenAI literacy is not a sprint, but a marathon, where even missteps contribute to the organization’s journey forward.
To do this, define your goals with the precision of a master craftsman. Knowing what success looks like enables you to recognize it upon arrival. Simplify use cases to clear the fog for decision making. Complexity is the siren that leads to indecisive drifts. Ownership must be as clear as a bell — without it, accountability is lost. Measure not just the destination, but the effort required for value versus cost and risk. As you embark on this expedition, remember to set a timeline to anchor your assessments, capture metrics that narrate your journey and remain vigilant for unexpected gains. And amidst all of this, ensure your GenAI sails are set with safety as the guiding star.
CIOs, according to Russell, should “play the long game in developing GenAI literacy and fluency in their organizations. There will be many paths, and some will be ‘failures’ but still advance the organization and its business objectives.”
For this reason, McMahon believes, “Organizations should be deliberate in what they need to achieve from the start. If they don't know what they want to measure, how will you know you've got there? CIOs need to be clear headed regarding who owns experiments and their outcomes. Lastly, they shouldn’t let scope creep ruin your day.”
Part of this, says Gildersleeve, is to “keep use cases simple. The more complex the pilot, the less likely to get to a decision on deployment. As far as learnings go, does the tool meet the need, is it improving a process, how difficult is it to deploy and what is the cost?
Hinchcliffe stresses that, “CIOs should take steps to ensure GenAI pilots produce outcomes that lead to deployment. Doing this is accomplished by capturing metrics and KPIs that tell the story, not assuming a fixed outcome, looking for all the benefits, including unexpected ones and lastly, putting guardrails on GenAI to make sure safe AI gets rolled out.”
This is especially the case for self-service GenAI to make sure that corporate intellectual property (IP) or personally identifiable information (PII) isn’t released.
Help for Organizations That are Late
In the race to integrate GenAI, being fashionably late to the party may just be a strategic mistake. With this said, what guidance and recommendations should be provided for those that are just getting started? CIOs say it is important to seek partnerships with vendors that are not just peddlers of AI, but collaborators in innovation. Together, they should set up data guardrails and ethical standards that stand as testament to your commitment to responsible AI deployment.
Russell says, “For some, a boot strap up can come from existing vendor partners. With their help, establish data safeguards and ethical standards. This is a big-tent moment. Find ways for all to be involved or informed.”
At the same time, CIOs should discard the temptation to chase after the AI zeitgeist. Instead, they should focus on where the rubber meets the road: what do your employees grapple with daily? These pain points are the hidden gems, ripe for the transformative touch of GenAI. Start by streamlining manual drudgeries — not with grandiose flair, but with the meticulous hand of a craftsman aiming for operational wins.
For this reason, Friedman suggests it is important that CIOs aim at creating more value for customers, employees and ecosystem partners, whether the value is operational efficiency, innovation or growth.
At the same time, CIOs should wade into the waters of GenAI with the enthusiasm of an explorer. They need not wait for the perfect use case to dip their toes in. Talk to those who've already navigated these waters, understand the utilities of AI they have uncovered and leverage their insights. For early endeavors, prioritize the urgent, the chronic and the expensive problems that GenAI can address swiftly — problems that have withstood the test of time and those that bleed resources. In doing so, you may discover that even for the latecomer, GenAI harbors opportunities to make up for lost time, turning the late into the strategic.
For this reason, McMahon argues, “Don't worry about catching up. Focus on getting going. Let your non-tech staff tell you what their problems are — that's where the quick wins are hiding. Just get out and measure time spent on manual tasks — don't try and be fancy on day one. Also, don't get caught up in the hype.”
Next, Gildersleeve suggests, “It is important to think about areas where you can pilot the public GenAI models to see what's out there. Talk to vendors who are releasing AI features. Most have examples from their own exploration or other customers. Don't worry about finding the perfect case. Just get started.”
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Finally, Hinchcliffe says, “look for projects that solve urgent problems — long-standing, unsolved problems — or solved problems that consume major OpEx to solve.”
Parting Words
As GenAI continues to permeate the corporate world, the strategy CIOs should pursue should be a measured approach and focus on internal use cases with transformative potential. Companies like Microsoft are pioneering with large-scale applications, such as ChatGPT and Copilot, while others should cautiously test the waters, embedding AI into operations, especially where user demand is palpable.
The goals should be a nuanced blend of optimism and pragmatism, where each step is geared toward efficiency, growth or innovation, without succumbing to the hyperbole that often accompanies new tech. For those developing a GenAI pilot, the key is to start with the end in mind: establish objectives, simplify use cases and safeguard data. Success should be framed not just by the end goals, but by the depth of the journey — measuring value against cost and risk.
With safety as the beacon, it's crucial to remember that GenAI is about enhancing tasks, not displacing the workforce, and ethical stewardship is paramount. Latecomers to GenAI can find strategic advantage by leveraging vendor partnerships and focusing on pressing, long-standing or costly issues, transforming tardiness into tactical opportunity.
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