Fur-tastic Future — Zoetis Leads the Charge in AI-Powered Animal Health Solutions

Interview with Krishna Cheriath, Chief Data and Analytics Officer, Head of AI at Zoetis.

When thinking about pet or animal care, Artificial Intelligence (AI) might not be the first thing that comes to mind. But, as in many other industries, advancements in machine learning and more sophisticated technologies are increasingly influencing how we monitor, interact with, and care for our animals.

Zoetis, the global leader in animal health, distinguishes itself not only through its manufacturing of medicines and vaccines but also through its groundbreaking use of AI and data analytics to drive scientific innovation for optimal health outcomes. Their dedication to harnessing technology extends beyond conventional limits, serving a broad spectrum of customers, from pet owners fostering the human-animal bond to improving health outcomes for livestock.

Leading this effort is Krishna Cheriath, Chief Data and Analytics Officer (CDAO) and Head of AI at Zoetis. He manages a global team responsible for various areas across the company’s biopharma value chain, including digital products and services, AI, analytics and data science, intelligent automation, data strategy, data governance, and digital solutions.

Cheriath recently spoke with Ben Blanquera, Vice President with Rackspace Technology and CDO Magazine Global Editorial Board Member, about the challenges involved in overseeing one of the industry's most expansive digital infrastructures and the crucial role of optimizing AI to drive innovation in animal health care.

Playbook takeaways:

  1. Automation: Utilizing automation allows human resources to focus on tasks that demand strategic insight and creativity.

  2. Value-focused diligence: Align AI initiatives with the company's highest priorities and demonstrate their tangible value.

  3. Emphasize human adoption of technology: Balance technical innovations with a deep focus on human needs, acknowledging that the ultimate success lies in serving human interests and aspirations.

  4. Develop an experimentation mindset: Embrace experimentation, recognizing that navigating digital disruption requires humility and a willingness to continually learn and adapt in an evolving landscape.

  5. Approach AI with humility: Recognize that AI is an ongoing journey, brimming with discoveries yet to be made. Approach it with humility and a willingness to adapt and grow.

Implementing a Venture Capital model to accelerate AI

AI has played a crucial role at Zoetis in pioneering innovative diagnostic solutions and propelling the field of animal healthcare forward. While the company has already established itself as a leader in disease detection and predictive analytics, it is also exploring the application of AI in drug discovery and clinical development.

To enhance AI use cases as an enabler, Cheriath formed cross-functional “Explorer” teams, drawing inspiration from his favorite Netflix series "Drive to Survive." These teams, named after Formula 1 racing teams, were tasked with discovering both external and internal opportunities for AI use cases.

Externally, Cheriath says the teams engaged with thought leaders, subject matter experts, big tech, venture capital, and startups to grasp the rapid changes happening outside the company. The teams then identified priority use cases focusing on R&D, commercial, and sales and marketing, particularly in generative AI and traditional AI. Internally, the team explored which areas were most important to the business. 

The program Cheriath created invests in these endeavors, utilizing a venture capital approach. “We allocate series A funds for promising proof of concepts that align with our seven identified use cases, and we set clear exit criteria based on technology and value feasibility,” he says. “Like traditional venture capital investments, we expect some proof of concepts to succeed and some to fail. The successful ones are developed further to scale with a strong focus on adoption and change management.”

Operationalizing AI

Zoetis prioritizes both “human ops” and AI/ML ops to effectively scale solutions. Human ops focus on understanding user needs and ensuring AI solutions align with their tasks and responsibilities. AI/ML ops ensure technical proficiency, model maintenance, and robust enterprise capabilities such as model registries and ROI measurement.

Cheriath strongly believes that AI won't replace humans, but rather that humans leveraging AI will drive significant advancements. When computers were first introduced, he says, individuals with computer skills outperformed those without. Nowadays, proficiency in computer usage is considered standard for knowledge workers. Similarly, AI is on a trajectory to become an integral part of today’s professional landscape.

However, simply proving the technical capabilities of AI isn't enough. The key lies in human adoption and user experience. “If AI tools aren't embraced, trusted, or integrated into workflows effectively, human potential remains unrealized. Therefore, operationalizing AI requires a focus on human adoption and front-loading the user experience,” says Cheriath.

In the past, many IT or digital projects failed to prioritize change management and user adoption, relegating them to the last slide of presentation decks. Cheriath says, “We must proactively design strategies to gain human buy-in, foster trust, and provide training.”

Scaling AI initiatives also demands robust enterprise capabilities. Adopting a "think big, start small, run fast, and scale well" approach, Cheriath emphasizes the importance of foundational elements such as model registries and rigorous model maintenance, treating AI models as valuable assets deserving of proper management and upkeep.

Culture and collaboration

To drive innovation effectively across Zoetis’ numerous businesses, Cheriath underscores the importance of fostering cross-functional collaboration and aligning the company's strategic priorities across departments. By securing buy-in from key experts and leaders in these areas, businesses can accelerate progress and outpace competitors.

This requires a culture of innovation collaboration and streamlined processes, known as the minimum viable bureaucracy approach, to ensure efficient engagement and decision-making across different expertise areas and address systemic challenges within the company.

Cheriath fulfills the role of a "boundary spanner," blending his skills as a business strategist, digital and AI strategist, technologist, and communicator. He says, “This multifaceted approach helps to build trust among team members and facilitate effective collaboration.”

Inspired by the book "Decisions over Decimals," Cheriath prompted his business leaders to complete the sentence: "I wish I knew, or I wish I could." This exercise underscores the importance of combining business expertise, operational insight, and subject matter knowledge to identify current challenges and opportunities. It emphasizes the inclusion of perspectives from individuals proficient in digital technologies and AI, yet unfamiliar with the specific context.

US Army: Data Leadership Pilot Program 

Beyond his responsibilities at Zoetis, Cheriath serves as an adjunct professor at Carnegie Mellon University (CMU) and the Rutgers Business School. He played a significant role in co-designing a Chief Data Officer certificate program at CMU. Now in its fourth year, this program offers ambitious Chief Data and Analytics Officers invaluable insights and practical experiences from seasoned professionals. 

The certificate program has also led Cheriath, along with his fellow professors at CMU, to collaborate with the U.S. Army on a pilot initiative on data-driven leadership, initiated by the Army’s Chief Data Officer. Cheriath and the Executive Education team at CMU developed a program aimed at equipping Army leaders with essential data-driven decision-making skills.

Given his father's service as an Army medic, Cheriath says this collaboration holds special significance for him: “Because of my dad, I am proud to contribute to the Army’s mission.”


AI-driven tasks such as content creation, translation, and co-pilots are becoming standard practice – a natural and inevitable component of the digital evolution of businesses. Looking ahead in the short term, we should expect companies to face unique AI challenges and opportunities, resulting in technical hurdles but also gains in effectiveness and efficiency, alongside cost savings. Over the longer term, as AI becomes increasingly commoditized, standardized, and commercialized, these tasks will likely become practices rather than strategic advantages.

About Ben Blanquera

Ben Blanquera is a Vice President with Rackspace Technology. Rackspace is a global leading multicloud services provider with specialties in Data/AI, Application Development, Security and Cloud Platform. Blanquera is passionate about creating amazing business outcomes by leveraging data, analytics, and AI. He is on the CDO magazine editorial board and is interviewing global CDOs to gain their insights to create “playbooks” for the industry.

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