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Piloting a Gen AI Program? First, Pick the Right Ecosystem Partners

As companies make the investment to launch efforts, they wonder how to get meaningful and sustained returns.

Steve Smith

December 27, 2023

3 Min Read
Gen AI program piloting tips
SomYuZu/Shutterstock

Powerful generative AI-based applications are changing how work gets done — challenging enterprises to build the in-house tech, organizational foundations and governance needed while reskilling workers to meet the opportunity.

The solution: Picking the right ecosystem of partners to help innovate and modernize with AI.

You'll learn quickly your efforts require a multivendor approach because of generative AI's reach as a corporate connective tissue.

According to Keri Dawson, head of solutions and offerings at Wipro, experienced business partners can help clients evolve and adopt this new technology, but businesses also can fundamentally evolve how they operate and deliver client services in terms of efficiency, automation, and unlocking new services through GenAI, especially in domains that rely heavily on creativity and content generation, like sales and marketing, or code testing and generation.

No organization can deliver those outcomes alone. They don't have the technical depth, business acumen or global reach. With big decisions at play, consultancies and systems integrators have an important role providing the skills, training and guidance creating a platform to drive responsible, transparent and explainable AI workflows.

Build a Competitive Advantage, Quickly

With its ability to extract essential information from unstructured data and create original content based on that information, generative AI can increase cost efficiency and productivity.

Generative AI-rooted applications can help call centers improve service and enable human agents to focus on more complex tasks. Engineers use it to generate starter code and for code modernization. HR departments are embracing generative AI to manage their workloads. But knowing the right use case takes insight, and that's where experienced business partners come in.

"We are working with a client that is concerned that if the company doesn't change its business model rapidly and embrace AI, it will be out of business in five years," said Tara Whitehead Stotland, leader of strategy and innovation at Cognizant Consulting. "There's a high probability that's true."

A Solid Foundation, Reskilled Workers

The key to businesses' differentiation in AI is customizing the technology to a customer's needs. That's why it's critical to get foundational models right.

The road to generative AI begins with large language models (LLM) trained on business-relevant data sets from five domains — internet, academic, code, legal and finance — that are tuned to an enterprise's unique data and domain knowledge. Enterprise users require high accuracy and reliability as well as the ability to navigate through siloed data in complex formats. Meanwhile, everything must be guided by principles of trust and transparency.

Business leaders face a host of talent-related challenges regarding AI, from the skills gap to shifting employee expectations. This is a pivotal moment for leaders to define the organization's transformation strategy and how people — and AI — work to deliver it.

The Shift to an AI-First World

We're at an exciting inflection point for generative AI. In less than a year, we've gone from the "run your business and apply AI to help" paradigm to enterprises navigating how to embed AI into the fabric of strategies. No one generative AI platform will rule. Just like a hybrid cloud approach is a key enabler of AI, they will need a hybrid AI strategy, guided by partners with expertise across multiple domains and technologies.

Now is the time to get it right. As businesses tread unfamiliar territory, they need assurance the AI used for mission-critical decisions and outputs is trustworthy, ethical and reliable. It must be designed to be explainable, fair, robust and transparent. And it must prioritize and safeguard consumers' privacy and data rights to engender trust. At the same time, organizations must implement AI within an environment upholding governance to effectively navigate the complexities of regulatory and compliance demands.

To reach this land of opportunity, we'll need a solid partner ecosystem. Let's embrace the future of generative AI — together.

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About the Author(s)

Steve Smith

General Manager, Global Systems Integrators, IBM

Steve Smith is the general manager for global systems integrators at IBM. He previously was general manager, IBM Cloud & Cognitive Software for the Americas, where he was responsible for a team of more than 3,000 software sales, technical, ecosystem development and services professionals. Before that, he was responsible for IBM's software business in Europe.

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