In the vast landscapes of agriculture, where innovation meets the earth, the Syngenta Group stands as a towering force—a $33 billion conglomerate with a profound impact on crop protection, herbicides, insecticides, fungicides, and seed innovation. As we delve into a conversation with two of Syngenta’s senior leaders, Roland, the Head of Corporate IT, and Feroz, the CIO and Chief Digital Officer, we unearth not only the specific AI strategies propelling their industry but also universal insights that can guide CXOs across diverse enterprises in their AI journey.
1. Innovation Rooted in Generative AI:
Feroz paints a vivid picture of how AI becomes the brushstroke of innovation at Syngenta. From chemistry to genetics, generative AI catalyzes groundbreaking research, ushering in a new era of differentiated products and services for farmers. The exploration of generative chemistry, an intersection of AI and chemistry, is poised to reshape research cycles, from lab to field. The influence of AI transcends the laboratory, venturing into the fields where decisions in the agricultural calendar unfold. AI emerges as the silent partner in farmers’ choices, from seed varieties tailored to soil and weather conditions to nurturing crops through the season until the harvest. It’s a testament to AI’s core role in bridging the gap between theoretical innovation and practical, on-the-ground decisions.
2. Operational Excellence Amplified by AI:
Roland reveals how AI aligns seamlessly with Syngenta’s strategic pillar of operational excellence. The focus on productivity and employee experience unveils a dual strategy. Automation, driven by AI, propels efficiencies, with tangible outcomes such as saving thousands of work hours. The emphasis on employee experience, a vital but often overlooked dimension, underscores the transformative potential of AI in enhancing workforce dynamics.
AI becomes the catalyst for a proactive, automated, and simplified work environment, aligning with the expectations of a new generation workforce.
CTA: Curious to hear Roland and Feroz dive deeper into how AI transforms operational excellence? Unlock exclusive AI insights in our podcast conversation!
3. Pillar-Focused Innovation:
Feroz introduces a strategic trifecta—Innovation, better customer experience, and productivity. This triad serves as the litmus test for potential AI use cases. The focus is clear, aligning with the pillars ensures that AI applications contribute to innovation, enhance customer experience, or boost productivity.
4. Internal Crowdsourcing – The Syngenta Shark Tank:
A unique facet of Syngenta’s approach is the internal crowdsourcing of innovation. Echoing the popular television show, the organization adopts an internal Shark Tank model. Ideas flow from every corner of the 50,000-strong organization, providing a diverse pool of perspectives. The impact and feasibility of these ideas, as presented by the contributors, become pivotal in deciding which innovations to nurture.
5. Feasibility and Value Potential:
Roland unravels the classic dimensions of feasibility and value potential. Navigating newer fields requires a keen eye on reasonable value potential coupled with a high likelihood of success. This strategic starting point is rooted in experimentation—embracing a fail-fast philosophy. Quick experiments and pilots become the litmus test, allowing stakeholders to comprehend the technology’s capabilities, limitations, and, most importantly, its potential business impact. This iterative process ensures a dynamic, responsive decision-making environment, where the organization evolves in tandem with the rapidly changing technological landscape.
Roland contends that this approach allows everyone involved to gain insights into the technology—what it can achieve and where its limitations lie. The collective understanding becomes the bedrock for informed decision-making on the feasibility and readiness of adopting specific technologies.
6. Intersection of Core Domain and Technology:
Feroz establishes a fundamental principle—the intersection of the core domain and computer science. The unique space where chemistry, genetics, and agronomy converge with AI, deep learning, and neural networks forms the epicenter of decision-making. This delicate balance is an art Syngenta has mastered, strategically choosing to build internally when the core domain is critical to business success.
Syngenta’s commitment to marrying domain expertise with cutting-edge technology birthed a unique entity—Computational Agronomy. This team serves as the bridge between computation and agronomy, seamlessly integrating new technologies into the hands of agronomists and farmers. It’s a testament to Syngenta’s vision of internal collaboration propelling innovation in critical areas.
Feroz underscores the importance of the core domain in determining the “build” strategy. When the expertise in chemistry, genetics, or agronomy becomes business-critical, Syngenta opts to build internally. The creation of specialized teams underscores their dedication to pushing forward internal domain expertise using the formidable tools of computer science and AI.
7. Enterprise Solutions and Collaboration:
Not all challenges demand an internal solution. Roland elucidates the practical approach—identifying problems that are similar across industries and acknowledging that an efficient, compliant, and streamlined company operation is a shared goal. Syngenta’s “buy” strategy involves partnering with external partners and leveraging platforms outside for seamless integration.
Roland’s strategic approach to partnering is underlined by a thoughtful consideration of buying capabilities. From infrastructure to specialized services, the synergy between in-house configuration and externally sourced platforms demonstrates Syngenta’s commitment to adopting a holistic strategy in achieving operational excellence.
8. Addressing Adoption & Job Impact Concerns:
Feroz acknowledges the elephant in the room—resistance to AI due to job impact fears. Syngenta’s strategy doesn’t shy away; instead, it showcases the tangible benefits of AI in the agricultural domain. The computational agronomy team’s sophisticated algorithm, considering soil conditions, weather forecasts, and historical yield data, not only provides personalized recommendations but becomes a transformative tool in seed selling.
The journey toward strategic AI adoption at Syngenta involved practical demonstrations and extensive pilot programs. By engaging agronomists in a thorough pilot phase, the organization showcased the algorithm’s superiority over traditional methods. This hands-on approach, coupled with success stories, built trust and conviction within the organization, turning the AI system into a cornerstone of their seed-selling approach.
Successful adoption wasn’t a solo act. Collaboration with key stakeholders, especially experienced agronomists, played a pivotal role. By involving them in the pilot phase, addressing their initial hesitations, and showcasing the algorithm’s prowess, Syngenta secured buy-in from the core users. This collaborative strategy proved instrumental in scaling the technology.
CTA: Discover how Syngenta conquered AI resistance and job impact fears. Dive deep into our podcast for the full story!
9. Longer-Term Upskilling Strategies:
Roland outlines the longer-term journey toward upskilling the workforce. Syngenta’s AI Accelerator, a 10-day hands-on training program, aims to make employees not just proficient but efficient in using AI tools. The program’s dual focus on imparting practical value and exposing participants to technology directly positions Syngenta at the forefront of AI readiness.
The AI Accelerator isn’t just about skill acquisition; it’s a holistic approach. Beyond efficiency gains, it addresses the psychological aspect of embracing AI. Exposing employees to the technology mitigates fear and fosters a deeper understanding, essential for widespread acceptance. This approach, currently in pilot, reflects Syngenta’s commitment to a carefully crafted transformational journey.
Roland emphasizes the importance of exposing the workforce to technology, reducing resistance and demystifying AI. By allowing employees to experience tools like Chat GPT and generative AI, Syngenta is not just upskilling; it’s sensitizing its workforce. This nuanced AI strategy not only addresses risks associated with new technologies but cultivates a workforce that embraces innovation.
The synergy between teaching practical skills and fostering sensitivity demonstrates a pragmatic approach. Syngenta acknowledges the human side of technology adoption and crafts interventions that balance the need for efficiency with the psychological aspects of embracing responsible AI.
10. Strategic Recommendations for CXOs
Roland, the head of corporate IT at Syngenta, offers three pragmatic recommendations tailored for CXOs and leaders venturing into the realm of artificial intelligence:
Define Target Impact:
Inaugurate your AI voyage by meticulously defining the target impact. Craft a robust framework that delineates the envisioned influence of AI investments on customers, employees, and the core innovation of your products and services. This clarity becomes the compass guiding your strategic decisions in these pivotal areas.
Avoid Hype, Focus on Outcomes:
Amidst the cacophony of hype and trends in the rapidly evolving generative AI landscape, maintain a steadfast focus on outcomes. Resist the temptation to be swayed by every emerging trend. Instead, concentrate on the key outcomes your organization seeks to achieve. Navigate the landscape with a discerning eye, concentrating on tangible solutions that deliver genuine value.
Embrace Experimentation:
Given the novelty of generative AI, embrace a culture of experimentation. Rather than committing to protracted transformation programs, conduct agile experiments to gauge feasibility and potential costs. Be willing to venture into uncharted territories, and based on the results of these pilot endeavors, make informed decisions on where to strategically invest for the long term.
CTA: Want actionable AI strategies? Roland’s insights go beyond this article. Hear them firsthand on our podcast.
11. AI Insights for Startups and Innovators
Feroz, the CIO and Chief Digital Officer at Syngenta, shares a compelling message for those embarking on this transformative journey:
Dream Big with Purpose:
“To startups and innovators, I say, dream big, but let purpose be your guiding star.”
In the vast landscape of AI, where possibilities are immense, it’s essential to anchor your dreams in a clear purpose. Understand the genuine challenges—local or global—that your technology can address. This purpose-driven approach not only gives your endeavors meaning but also resonates more profoundly with stakeholders.
Distinguish Your Idea in the Crowd:
Amidst the fervor surrounding AI, it’s imperative to distinguish your idea from the rest. Avoid being swayed by the current trends in generative AI. Instead, focus on crafting a solution that stands out by addressing a specific problem innovatively.
“The technology holds immense potential, but success lies in the unique value—what I like to call the ‘mote’—that your solution brings to the table.”
Focus on Real-World Problem-Solving:
The true impact of any innovation is realized when it solves real-world problems. For us, this was the path of AI and agriculture, and we kept our focus sharp on addressing tangible challenges faced by farmers, agronomists, and the agricultural ecosystem.
By aligning your vision with real issues, you position your solution as not just a technological marvel but a practical and transformative tool.
Early Engagement with Customers:
Success is not a solitary endeavor. Early engagement with customers is not just a recommendation; it’s a strategic imperative. Comprehend their problems intimately, walk in their fields, understand their workflows, and build solutions that seamlessly integrate into their daily operations. This collaborative approach not only refines your solution but also establishes a foundation for successful, long-term partnerships.
In conclusion, the Syngenta dialogue offers rich AI insights for CXOs embarking on a digital transformation and automation journey. From strategic AI innovation to internal crowdsourcing, from agile experimentation to addressing workforce concerns, these lessons carve a path for enterprises to thrive in the transformative landscape of AI and agriculture. As we harvest these AI insights, the fields of opportunity are vast, waiting for leaders to sow the seeds of technological advancement and reap the fruits of strategic AI integration.
