Applied AI: Nix Order Takers and Demand Strategic Partners

There is undoubtedly strong momentum in AI infrastructure buildout, as evidenced by the market valuations of players like NVIDIA, but there is a critical gap in the market that is limiting AI-driven value creation.

Arguably the biggest hurdle in realizing AI's business potential is not technology. It is inherently human: strategic acumen. It is about having human leaders who hold the clear understanding and sharp judgment needed to use AI effectively to meet business goals.

After decades of customers being savvy enough to tell vendors exactly what they want, the landscape has shifted. Now, possibilities are outpacing understanding. Businesses are eager to apply AI but largely do not know what is possible, how to start, or if they do have a strong AI environment already, they are struggling to mature it. Let us check out some real-world examples to give you more context.

Real-World Examples

Walmart

Consider the retail giant, Walmart. They have been investing heavily in AI to optimize supply chains, improve customer experiences, and personalize marketing efforts. While they have made significant strides, the true value of these investments comes not just from the technology itself but from the strategic guidance they have received from their partners. Walmart did not simply adopt AI tools. They worked closely with their technology partners to align AI capabilities with their business objectives, resulting in measurable improvements in efficiency and customer satisfaction.

A standout example is Walmart's use of AI for route optimization. Their AI solution optimizes driving routes, packs trailers efficiently, and minimizes miles traveled, resulting in significant reductions in emissions and costs. By using this technology, Walmart avoided generating 94 million pounds of CO2 and optimized routes to bypass 110,000 inefficient paths. This success showcases how effective technology partnerships can drive both cost savings and environmental benefits, demonstrating that AI's impact can extend well beyond the bottom line.

Healthcare

On the other hand, we see industries like healthcare, where the potential for AI is immense, but adoption has been slower despite 90% of surveyed healthcare leaders expecting that AI adoption will help make or break their institution's success over the long-term (January 2024 findings). Hospitals and healthcare providers often have access to advanced AI technologies for patient care and operational efficiency. However, the lack of strategic technology guidance desperately needed to address their situational complexities has led to underutilized AI tools, with many pilots never transitioning to full implementation. The result? Missed opportunities to improve patient outcomes and streamline operations.

JPMorgan Chase

JPMorgan Chase (JPMC) has been at the forefront of using advanced AI technologies, including large language models, to tackle some of the most pressing challenges in financial services. One of the key areas where AI has made a significant impact is in fraud detection. By using AI to extract entities from unstructured data and analyze them for signs of fraud, the bank has achieved a 50% reduction in false positives and a 30% increase in the detection rate of actual fraudulent activities.

In addition to fraud detection, JPMC has successfully integrated AI into its trading operations to improve efficiency and reduce costs. AI assists in payment validation screening, reducing false positives and enabling better queue management. This has resulted in lower levels of fraud and an improved customer experience, with account validation rejection rates cut by 15-20%. The success of these initiatives is not just a result of the technology itself but also the bank's collaboration with partners.

Identifying the Right AI Partner: Key Characteristics

When choosing a technology partner to help you realize the full potential of AI, it is essential to evaluate them based on key characteristics that indicate strong strategic acumen and the ability to deliver real business value. Here are the top traits to look for in an AI partner:

1. Unique Expertise and Knowledge: A valuable AI partner should possess deep expertise not only in AI technologies but also in how to strategically apply these technologies within your specific industry. They should have a proven track record in AI implementations and a comprehensive understanding of both technical and business processes.

2. Proprietary Tools and Methodologies: The best partners bring more to the table than just off-the-shelf solutions. Look for those who have developed proprietary tools, frameworks, or methodologies that provide a competitive edge.

3. Strong Industry Reputation: Reputation matters. A partner with a strong market presence and positive client testimonials is likely to be more reliable and effective.

4. Access to Specialized Talent: AI initiatives require a broad range of skills, from data science to machine learning engineering, and more. Ensure your potential partner has access to a pool of specialized talent who can bring valuable insights and expertise to your project.

5. Alignment with Business Goals: The ideal AI partner should be able to clearly align their AI solutions with your specific business goals. They should offer customized roadmaps that not only integrate AI into your operations but do so in a way that directly contributes to achieving your strategic objectives.

6. Proven Ability to Drive ROI: Results speak louder than words. Seek out partners who can demonstrate a strong track record of delivering measurable business value through AI.

7. Adaptability and Innovation: The AI landscape is constantly evolving, so your partner should be adaptable and innovative. They should be willing to explore new ideas and approaches, and capable of tailoring their AI solutions to the changing needs of your business and market conditions.

8. Long-Term Partnership Potential: AI is not a one-time project but an ongoing journey. Look for partners who are committed to a long-term relationship, offering continuous support, and iterative improvements.

9. Resource Availability and Stability: Niche partners teamed with larger partners or functioning as part of a specialized AI partner ecosystem offer the best of both worlds. Niche partners bring focused expertise, agility, and tailored resources, while larger partners provide financial stability and broad access to AI supporting infrastructure.

10. Cultural and Strategic Fit: A good cultural and strategic fit is essential for effective collaboration. Your partner's work culture, communication style, and strategic approach should resonate with your organization's values and goals.

The Way Forward: From Order Takers to Strategic Advisors

Armed with this knowledge, where do you go from here? Unfortunately, many technology partners lack the characteristics that I have shared and are content to play the role of order takers, unprepared to proactively guide clients through these complex challenges. Even worse, their entire go-to-market approach has been optimized for waiting on clients to do the heavy mental lifting for them. This passive stance is causing significant delays in AI adoption and value realization, slowing the critical transition from prototype to full implementation.

Technology partners must stop expecting to simply take orders and start acting as strategic advisors, bridging the gap between AI capabilities and business needs. This shift is crucial for moving from the infrastructure buildout phase to realizing productivity gains.

Proactive, knowledgeable strategic guidance that enables high-quality decision making is more critical than ever. It is not enough to build the infrastructure; we must ensure that businesses can use it to its fullest. It is time for technology partners to stop expecting customers to do the mental heavy lifting. Stop waiting for orders. Instead, start actively engaging with customers as strategic advisors, working together to identify and implement real-world, business value-driving solutions. This collaborative approach ensures that AI capabilities address real business needs, paving the way for successful implementations that deliver tangible results.