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4 GenAI tips to accelerate your success

Stephanie Shine, Jared Johnson
Chairs and table in a boardroom

“Help! Our GenAI use cases are too boring for the boardroom!”

GenAI is a hot topic today, but it’s important to remember we have been working with AI since the 1950s and utilizing it to catapult digital transformation generation after generation. There’s a lot to learn, but also plenty of historical knowledge to lean on. We asked Kin + Carta experts to share their top GenAI advice to ensure you can embrace this attention-grabbing tech in the most meaningful ways. 

1. Start with common ingredients to create a winning recipe:
While so much about GenAI feels new, we can learn from solutions we have cooked up before.

"As a leading provider of industrial AI systems, the team at Kin + Carta has been behind myriad successful deployments of generative AI systems into enterprise contexts for years. The same tenants that were true in the world before GPT, apply today, though arguably at greater scale. The elements of excellent GenAI, and more broadly AI/automation systems have these common ingredients: governance, provenance, quality, scalability, and extensibility. We work every day to work through challenges to create bullet-proof data foundations to ensure accuracy and sustainability." 

–Cameron Turner, VP Data Science

“Generative AI provides both an opportunity to create novel features and to make it easier, cheaper, and quicker to get existing work done. In either case, though, organizations need to ready their workforce and teams. This means leveraging teams closest to the problem sets to figure out business-positive use cases. Then, providing the tooling, guidance, and training—as well as experimentation time—for all teams to embed these solutions into their regular workflows over time.”
–Joe Nedumgottil, Technical Director, Cloud Practice Lead

2. Avoid buying a hammer to search for a nail:
Identify business problems and align them with the right solution to build (which might not be GenAI).

"A major pitfall that we are seeing leadership make is approaching GenAI as a solution in search of a problem. This often results in building the wrong solutions for technology's sake. We need to realign priorities by continuing to focus on fundamental data strategy for organizations while up-skilling teams on GenAI. A problem first and customer-centric approach should be taken and it is completely okay when GenAI is not the solution."

–Dhyaanesh Mullagur, Technical Principal

“With GenAI, like in other domains, the Socratic "know thyself" is still true. C-suites have to be honest about what LLMs can and cannot do and what is right for their organization. Is it better for your organization to pursue practical, unsexy use cases that save time and reduce opportunity costs or to ‘moonshot’ for top-line revenue? In either case, the ROI must be well-defined and the internal friction to execute explicitly known.”

–Thomas Fisher, Director, Client Engagement

3. Remember, science is magic and magic is science:
Development succeeds most often through data-driven decisions and iterative, hypothesis-based experimentation.

“Resist the urge to cherry-pick narratives and let your data illuminate the path forward. Don't hastily base product decisions solely on a few conversion metrics. Leverage the indispensable basics of data literacy and empower your teams to make data-driven decisions. By utilizing the available data, GenAI becomes a transformative force, unlocking innovative, high-value solutions as you embark on the development journey.”

–Josh Wu, Product Principal

“Innovating will inevitably come with trying something and falling short of the desired outcome, and that is part of the iterative process that is innovation. Creating an environment where those shortcomings are all just viewed as a learning opportunity is really important. And when an innovator does achieve some notable success, celebrating that success is really important.”

–Brad Tagtow, Technical Principal

4. Acknowledge the unsung human heroes and include them in your planning:
Attention to people and process is fundamental to realizing success.

“Often overlooked is the significant role that user experience plays in GenAI projects. The final outcome of these projects invariably involves user interaction, serving both as instructions for the machine and as a means to view its output. A UX practitioner contributes to machine training by crafting prompts that emulate user interactions, while also designing the presentation of the machine's responses.”

–JB Leach, Director - Experience Design

“Data foundations are not just critical to how organizations advance their GenAI capabilities but also in how we bring the people along on the journey in embracing GenAI. We are doing the work to ensure there’s quality and trusted data that’s accessible for data consumers. We are establishing data ownership within the business. Once the people have the power of data in hand to improve decisioning within the organization, they can begin to wrap their minds around what’s possible with GenAI and opportunities for improving work today. The sooner companies bring the people along on the data journey, the further we will go with GenAI.”

–La-Neisha Pridgen, Data Strategist

Discover the reality of GenAI and its potential to revolutionize businesses

Read the full article here

What now?

As the buzz around GenAI continues to grow across C-suites worldwide, leaders must channel energy into fostering a culture that appreciates both the grand and granular aspects of GenAI implementation. Instead of dismissing less glamorous applications, organizations should view them as building blocks for future innovation, recognizing the value of insights gained from each step in the GenAI journey.

This iterative approach paves the way for sustainable and impactful GenAI integration for years to come. And what’s more exciting than that?

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