Sumit Johar is the Chief Information Officer at BlackLine.
Today, AI deployment feels a bit like a galaxy: vast, unpredictable and constantly expanding. Just like the Guardians must navigate uncharted territories, CIOs are tasked with charting a course through the AI evolution, balancing innovation with responsibility to ensure their organizations thrive.
Concerns about data quality, compliance and the rapid pace of AI advancements have created hesitancy, particularly when AI is hastily deployed into customer-facing applications. Despite these concerns, the momentum is undeniable: According to the KPMG Global AI in Finance report, 71% of organizations are already using AI in their finance functions, with this figure expected to climb to 83% in the next three years. Early adopters are already seeing strong results, especially in financial reporting, where AI is reshaping traditional workflows. As Groot might put it: “I am AI”—a powerful force but one that needs the right team to truly thrive.
The answer lies in a measured, iterative approach to AI deployment. Internal innovation labs run by CIOs offer a safe environment for testing and refining AI tools before scaling them across an organization. These labs allow IT leaders to guide their teams through the complexities of AI adoption while delivering results that align with business priorities, before working with the CTO to distribute these capabilities at scale.
Innovation Labs: From Concept To Impact
CIOs play a crucial role in leveraging technology to create differentiation. This is not limited just to the products a company offers; it extends to the enterprise’s overall operations and customer experience. Particularly in the SaaS-driven subscription economy, it’s no longer enough to provide a great product—the entire customer journey must be exceptional.
From onboarding to post-purchase support, and even interactions with sales reps for repeat business, every touchpoint matters. CIOs are increasingly involved in ensuring these end-to-end experiences are seamless.
This demands a cautious approach to AI, where tools are tested thoroughly before wider or customer-facing implementation. One approach is to test AI in low-risk environments, such as internal innovation labs, to build confidence among employees and ensure alignment with organizational strategy.
For instance, our company launched a BlackLine-GPT internally called “Buckie” to test conversational abilities based on our own in-house data. We leveraged AI models hosted within our own environment, leaving no risk of data being accidentally shared with AI providers like OpenAI. Buckie’s implementation includes a comprehensive awareness campaign to remind employees of AI’s limitations and the importance of human validation. This responsible adoption allows us to finetune the model before we offer it to our clients or use it externally.
CIOs serve as both innovation evangelists and protectors of customer and employee data, and innovation labs provide the perfect environment for this process. They allow organizations to experiment with AI in controlled settings, build employee confidence and identify challenges early. By focusing on iterative improvement, these labs ensure that AI solutions are robust, scalable and aligned with business needs.
Co-Piloting The AI Cosmos: CIOs and CTOs
The partnership between CIOs and CTOs is critical to successful AI deployment, particularly in industries like finance and accounting, where trust, compliance and data integrity are paramount. Internal innovation labs provide a controlled environment to establish governance, refine data accuracy and ensure AI readiness before scaling. Once validated, the CTO can leverage engineering expertise to build a reliable, scalable AI platform that drives enterprise-wide adoption.
Our CTO often (and correctly) points out that AI is only as effective as the data it’s built on. It’s not just about amassing vast amounts of data; it’s about ensuring that data is clean, structured and optimized for meaningful insights. Without this foundation, AI risks becoming an expensive source of noise rather than a strategic tool for decision-making.
When it comes to data governance, three priorities take center stage: security, interoperability and scalability. Compliance with industry standards such as SOC2, ISO 27001, and other certifications remains a top focus for CIOs, CTOs, and CISOs alike. And yes, the CISO is another crucial member of the Guardians of the AI Galaxy team, ensuring that AI-driven innovations are not just powerful but also secure and resilient. But that’s a discussion for another installment.
From AI Experimentation To Bottom-Line Impact
While both CIOs and CTOs are deeply involved in technology, their focus areas differ. CIOs prioritize implementation and operationalization, while CTOs concentrate on building and scaling technological solutions. When these roles align through mutual respect and collaboration, the result is a technology-driven organization that can deploy AI efficiently and strategically.
By establishing a clear AI strategy, maintaining regular feedback loops from a buyer’s perspective, and fostering open communication, organizations can remain in tune with market needs and drive continuous growth.
Just as the Guardians safeguard the galaxy with strategy and teamwork, CIOs and CTOs must collaborate to ensure AI is deployed thoughtfully and strategically. By embracing a structured approach to innovation, they transform AI implementation from a high-potential experiment into an enterprise-wide advantage. Strong leadership today lays the foundation for a future where AI drives measurable business success.
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