Artificial intelligence (AI) is transforming industries, but its real impact comes from how companies use it in strategic partnerships. These collaborations drive innovation, speed up product development and create new market opportunities.
Co-innovation is a strategic necessity in today’s competitive landscape. Developing cutting-edge AI capabilities in-house is costly and time-consuming. However, by collaborating with other companies and looking beyond your industry, you can accelerate time to market, reduce costs and gain a competitive advantage.
co-innovation-partnerships-nbsp">4 keys for successful AI co-innovation partnerships
1. Identify synergistic strengths
Strengthen your positioning by partnering with those who offer complementary expertise. Think beyond traditional industry boundaries. Consider how these tech companies have collaborated with companies in more “traditional” industries.
Pfizer and Tempus: Revolutionize cancer treatment with AI
Pfizer partnered with Tempus, an AI-driven precision medicine company, to enhance its oncology drug development. Using Tempus’ extensive multimodal data and machine learning capabilities, Pfizer can accelerate drug discovery and improve patient selection for clinical trials.
Microsoft and JPMorgan Chase: Advance financial AI
Microsoft and JPMorgan Chase expanded their collaboration to develop advanced AI models for financial services. They have enhanced fraud detection and risk management systems by combining Microsoft Azure’s machine learning tools with JPMorgan’s proprietary data.
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2. Co-create the vision
Both companies must have a shared understanding of the problem they’re solving and how AI can help achieve their goals. AI is not the solution itself; it’s a powerful technology that enables solutions. These examples demonstrate how partners co-create and collaborate to solve real-world challenges using AI.
Walgreens and Verily: Improve medication adherence with AI
Walgreens partnered with Verily (an Alphabet company) to address the issue of patients missing medication doses. This is estimated to cost healthcare systems $100 to $300 billion annually. By combining Verily’s AI capabilities with Walgreens’ patient data, they can predict and prevent missed doses, improving patient outcomes and reducing healthcare costs.
BMW and NVIDIA: Optimize car production with a virtual factory
BMW partnered with NVIDIA to enhance factory planning and operations with AI. Together they created a virtual factory, a digital twin of BMW’s production facilities. This allows BMW to simulate production workflows, identify potential issues before the physical factory opens, and ensure smoother, more efficient operations.
3. Build and use shared data ecosystems
AI thrives on data. Partners must be willing to share data securely and transparently to maximize its potential. The following examples demonstrate the growing importance of data sharing in AI partnerships.
Walmart and Pactum: Automate supplier negotiations
Walmart deployed a chatbot powered by Pactum’s AI technology to negotiate with human suppliers. Pactum’s AI analyzes data from both parties to identify mutually beneficial outcomes and create customized proposals, leading to faster, more efficient negotiations. The chatbot runs 2,000 negotiations simultaneously — allowing Walmart to streamline procurement, reduce costs and improve supplier relationships.
Kraft Heinz and Google Cloud: Optimize efficiency with demand forecasting
Kraft Heinz formed a multi-year partnership with Google Cloud to use AI for deeper consumer insights and improved product development. Using Google’s AI demand forecasting, Kraft Heinz can analyze historical sales, product promotions and even macroeconomic factors. This data sharing allows Kraft Heinz to improve forecast accuracy, optimize production planning and reduce inventory costs.
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4. Pilot, iterate, scale
AI solutions often require an iterative approach. Begin with a pilot project to validate the partnership, gather data and refine the strategy. The following examples demonstrate the successful scaling of AI partnerships after impactful pilot programs.
Walmart and Symbotic: Automating distribution with AI
Walmart partnered with Symbotic to automate its distribution centers using AI-powered robotics. Initial pilot programs in select locations proved successful, demonstrating increased speed and accuracy. As a result, Walmart is expanding the technology to all 42 regional distribution centers.
Bayer and Google Cloud: Accelerating drug discovery with AI
Bayer’s pilot project with Google Cloud used AI to analyze vast datasets of genomic information and identify potential drug targets. This demonstrated significant potential for reducing drug development time and costs, leading Bayer to expand its AI initiatives to expand its AI initiatives in drug discovery and patient diagnosis.
Shape your future with AI
AI co-innovation partnerships are not just a trend. They represent a fundamental shift in how businesses operate and thrive. By forming these strategic alliances and applying these key principles, companies can unlock unprecedented opportunities for growth, efficiency and market leadership. The key question is not whether to embrace AI co-innovation but how to strategically use its potential to reshape your future.
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