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  • Writer's pictureLynda Koster

Generative AI in Business: From Theory to Practice

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In today's dynamic digital landscape, generative AI stands out as one of the most transformative technological advancements of our time. While many have been captivated by its potential, understanding its capabilities is only half the battle. The real challenge—and opportunity—lies in transitioning from sheer comprehension to actual implementation. This shift, from recognizing the promise of generative AI to harnessing its power in tangible business applications, will be essential if we are to prepare our organizations for the future. In this post, we'll explore the nuances of this transition, ensuring that business and marketing leaders are equipped to navigate and take steps to begin tapping into the vast potential of generative AI while managing risk.

You don't need to start with expansive implementations. For many, the wisdom lies in starting small—with experiments and pilots. Not only do they shed light on the practical nuances of generative AI, but they can pave the way for larger, more informed applications in the future.

Addressing Executives' Top Concerns

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In a recent article by BCG titled, What’s Dividing the C-Suite on Generative AI?, the authors highlight that despite the promise of Generative AI (GenAI), over 50% of executives still discourage its adoption, as indicated by their Digital Acceleration Index. Executives' reservations stem from challenges like limited traceability, the potential for poor decision-making, investment priorities, data security, and a skills gap.

While these are all valid concerns, we have found that there are ways to initiate smaller efforts to gain insights, refine strategies, and figure out ways to address concerns that get surfaced throughout the process. Taking a proactive approach to learning coupled with focused experimentation can prevent companies from lagging behind or, at the very least, becoming better informed and familiar with GenAI's capabilities to start.

Setting Clear Objectives for Generative AI

The journey into generative AI must begin with a destination in mind. It's essential to define what success looks like for your organization. This clarity forms the bedrock of your GenAI initiatives, ensuring they aren't just technologically advanced pursuits but also strategic endeavors that drive meaningful outcomes. Furthermore, it's important to ensure that the objectives set for GenAI are seamlessly aligned with the broader organizational strategies. By intertwining GenAI goals with the overall mission and vision of the company, businesses can ensure that GenAI not only augments capabilities but also propels the organization towards its larger objectives in a cohesive and integrated manner.

In my previous post, Leading in the AI Era, we reinforced the need to start with a strategic vision and governance model for GenAI. Together, they instill confidence while providing direction and guardrails to your team amidst constant technological shifts.

GenAI Use Case Essentials: From Problem to Solution

Before diving into GenAI solutions, it's crucial to identify and prioritize use cases where it can deliver the most value. Use cases act as blueprints, highlighting specific problems GenAI can solve and help inform a clear and actionable roadmap for implementation. By starting with well-defined use cases, businesses can ensure their initiatives have clear direction and purpose, reducing risks and maximizing ROI.

If you're embarking on your GenAI journey and aim to unlock the potential of this capability, it's crucial to educate yourself, experiment, and collaborate with emerging experts who are well-versed in this domain and your specific industry. As you enhance your team's skillset, you may choose to engage with a trusted partner who can guide you in developing use cases and utilize their libraries of relevant examples. For instance, we offer this at Growthential as part of our AI Strategic Suite.

Consider an example from a recent use case that we have applied across multiple efforts:

In one use case, we reduced a research process from several hours of effort, to just minutes. This not only solved one problem, but it also enabled us to quickly gather and apply the same approach and insights across multiple projects, freeing up our time for other strategic priorities. Reflecting on our own journey, had my business partner and I not implemented a GenAI strategy, established a governance model, fostered adoption, or encouraged our teams to experiment, learn, and engage with new releases over the past year, we would have remained unaware of such solutions or how to combine, integrate and leverage them.

Choosing the Right Generative AI Solutions

In the rapidly evolving world of GenAI, having a clear objective is the first step. However, identifying the right tools and solutions to achieve that goal is equally crucial based on where you are in your journey. This process begins with assessing the current capabilities and technological infrastructure, identifying existing strengths, and spotlighting gaps GenAI can fill. With a clear understanding of needs in hand, the task of evaluating GenAI vendors, tools, and platforms becomes more targeted and efficient.

In my last article, Beyond the AI Hype, we delved into the lessons learned from the previous internet and martech boom and highlighted the importance of adopting a pragmatic approach to GenAI. Drawing from past experiences, we continue to emphasize the tangible benefits of a measured approach to any technology integration.

Organizations should look beyond just features, considering the vendor's track record, scalability, integration capabilities, and alignment with the company's specific requirements. It's also advisable to adopt a pragmatic approach when diving into GenAI integration: start with pilot projects. I can't emphasize enough that by focusing on smaller, manageable implementations, organizations can test the waters, garner insights, and refine strategies, ensuring that when it's time to scale, the foundation is solid and the direction is clear.

Sequoia Capital recently updated its Generative AI Market Map last week. What I really like about this map is that it is organized by use case rather than by model modality. As they stated in Generative AI's Act 2,

"this reflects two important thrusts in the market: Generative AI’s evolution from technology hammer to actual use cases and value, and the increasingly multimodal nature of generative AI applications."

They also offer a generative AI infrastructure stack visual, which is worth digging into. You don't need to be a tech expert to acquaint yourself with this map. It provides a structured view of all that comes through your newsfeeds, aiding in refining your comprehension when collaborating with your technology partners.

To elaborate further on the emerging and diverse generative AI ecosystem, Divyansh Agarwal, a Senior Research Engineer on the Interactive AI team at Salesforce, makes a great point in Beyond the Blackbox: Shaping a Responsible AI Landscape. He points out that models like ChatGPT represent just a small part of the broader generative AI ecosystem. Agarwal emphasizes that as we explore the vast potential of generative AI, we are entering an era marked by enhanced human-AI interactions. To build end-to-end applications, our approach must not only focus on the AI model itself but also on the systems that manage user data, infrastructure, and the model lifecycle. He reinforces that this signifies a shift from traditional non-AI systems to a more integrated AI experience.

Building an Effective AI Team: The Essence of the Right Talent

Navigating the AI domain, particularly emerging fields like generative AI, necessitates harnessing the right talent. Generative AI, though relatively new to the masses, has seen rapid advancements, with some professionals diving deep and gaining experience through intense experimentation. I am finding that such immersion offers valuable insights into what is really possible today and can offer a longer-term view of the potential of what is to come.

The significance of a dedicated GenAI effort, whether through a specialized team or a focused approach to training and learning, cannot be understated. If building a team well-versed in GenAI isn't immediately feasible, it's crucial for organizations to prioritize training, learning, and pilots with clear objectives. These dedicated efforts, whether via teams or guided learning, are poised to adapt and respond swiftly to the evolving demands of our new reality.

Beyond technical prowess, a deep-rooted understanding of a company's ethos, customer base, and operational intricacies is key to a harmonized and efficient GenAI integration. While the journey to identify, train, and retain top talent or expertise might present challenges, the alignment, adaptability, and innovation they usher in are invaluable. A strong commitment to GenAI, whether through an in-house team, external experts, a combination of both, or a focused approach to skill development, signifies an organization's dedication to tapping into GenAI's potential and guiding its trajectory with clarity and purpose. What's important is that you get started.

AI Ethics: Balancing Potential with Responsibility

The rise of generative AI presents many opportunities; however, executives will need to champion ethical AI practices. Business leaders must address ethical issues such as data privacy, bias, fairness, transparency, and job displacement. Ensuring user privacy and adhering to regulations like GDPR is crucial due to AI's data dependence. Executives should actively counteract biases in AI training data and promote transparent models. As GenAI adoption increases, concerns about job losses grow, so a focus on employee development and change management will be critical.

Beyond these issues, AI ethics also involve system security, accountability for AI errors, environmental effects of AI training, potential monopolistic power, and misuse like deepfakes or surveillance. Some even warn of existential risks from advanced AI. Thus, business leaders should collaborate with experts and communities for responsible AI development and use.

This past summer, I had the privilege of meeting AI Ethicist Olivia Gambelin, the Founder and Chief Executive Officer of Ethical Intelligence. She spoke at the MAICON 2023 event this past July, emphasizing the centrality of human well-being, values, and trust in AI strategies. She explained that the foundation of a strategy should be people-centric because they are the creators and users of AI. Without team engagement and buy-in, AI initiatives will falter. Hence, fostering an open dialogue about AI, including its challenges, is imperative.

She publishes a quarterly tech ethics magazine, a journal of case studies of ethics at work. If you have time, download Issue 4 of Equation, The Business Case for Ethics is well worth the read.

The integration of GenAI is not a business-as-usual product launch. You must be present. It requires a deep commitment from leaders and their teams to engage in ongoing discussions.

Fostering a GenAI-ready Workforce

We can all relate to the barrage of information and new releases happening daily. As the GenAI frontier advances, so must the skills of those navigating it. Curating GenAI-focused training programs is no longer an option but a necessity for businesses seeking to remain relevant. In an earlier post, Unlocking Innovation and Fostering a Culture of Growth in the Digital Age, I emphasized the pivotal role of a continuous learning model in today's dynamic professional landscape. But beyond just curriculums, there's a need to instill a culture of continuous learning within organizations. Such a culture ensures that employees evolve with the emerging times and technology. This evolution and adaptability accentuate the dual advantages of reskilling: 1. maintaining a competitive stance and 2. fostering employee growth and retention.

The GenAI Feedback Loop: Measure, Learn, Adapt

It will be imperative not just to set your efforts in motion but to monitor and refine them continuously. As with any strategic initiative, this process starts by setting up well-defined key performance indicators (KPIs). These KPIs, tailored to an organization's AI goals, serve as a compass, indicating whether the GenAI projects are on the path to success or need recalibration. Beyond measurement, there's an inherent need to assess the ROI of GenAI projects on an ongoing basis. In an environment where GenAI capabilities are rapidly advancing, the value delivered by a project today might not hold the same significance tomorrow. Thus, staying vigilant about the return on GenAI investments ensures sustained relevance and impact.

The journey with GenAI, however, is not a linear one. It's iterative by nature. As projects unfold, there will be moments of reflection, learning from both successes and setbacks and adapting strategies accordingly. This cyclical approach ensures that GenAI initiatives remain aligned with changing business landscapes, delivering optimal value and driving innovation forward.

Final Thoughts

Based on how the last year has been, it is clear that this movement is not waiting for anyone. Whether we like how this was released into the world or not, it is here. We need to figure this out.

As we stand at the inflection point of the AI-driven era, it might seem overwhelming. The vastness of AI's potential, paired with the complexities of its implementation, can indeed feel daunting. But it's crucial to recognize the significance of this moment in time. We are at a pivotal juncture—a point where understanding meets action, where theory converges with practice.

GenAI is not just about technological adoption; it's about strategy, foresight, managing risk, and redefining our business models. This immense potential to reshape industries requires active engagement, ethical considerations, and strategic alignment. Though the beginning of the GenAI journey might appear intimidating at first, by maintaining focus and taking one step at a time, you can actively engage in this transformation to be able to navigate this wave and be better prepared for the future.

Interested in learning more about our AI Strategic Suite offering to help you along this journey? Reach out to us at Growthential for more information.


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