Leveraging Generative AI for Product Development & Strategic Growth
Introduction
Hype cycles promised that generative AI could revolutionize the workforce, reduce costs, and elevate workflows to unprecedented levels of efficiency.
If that’s the case, then why are so many organizations stuck in their GenAI journey? Adoption is slow, and returns are not being realized quickly enough. The most obvious use cases for GenAI are not moving the needle at the levels that matter most to the business. All the while, shrinking EBITDA margins are adding mounting pressures to achieve positive ROI.
In this white paper, KMS Technology will help organizations explore new possibilities and think bigger to make a more meaningful impact with GenAI. With a mindset shift and practical steps to get your roadmap ready, businesses and investors alike can move from stagnation to implementation. Read on to realize the actual gains of this disruptive technology and avoid the risks of the unknown.
Chapter 1: Rapid AI Advancement
AI’s Transformative Impact on Business Success
AI is advancing at an unprecedented pace and its implications for business are profound. AI’s capabilities have grown exponentially, transitioning from basic tasks like image recognition to complex functions such as video comprehension and reasoning. This rapid progression marks not just a technological evolution but a significant shift in how businesses can operate and compete.
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The development of image recognition, which took 12 years, followed by the achievement of reading comprehension in just two years, highlights the accelerating pace of AI advancements.
These impressive advancements have enabled businesses to see immediate gains in areas that are particularly reliant on language generation. This Coatue AI Full Report details a variety of GenAI case studies and highlights, including:
- LLMs enabled a 45% reduction in human-answered questions in a customer support setting
- 55% time savings were reported by developers using GitHub Copilot
- Patients rated 79% of AI chats as higher quality than physician responses
Additionally, many organizations have made use of GenAI for content creation and sales enablement, from writing and editing emails to drafting multiple campaign iterations. While these results and functionalities are impressive, these initiatives have not necessarily shifted the big picture for critical margins like EBITDA. These gains shouldn’t be left on the table; in fact, there’s an urgency to adopt at these elementary levels to maintain pace with the competition. However, there’s a scale to the exponential growth of GenAI that businesses must contend with if they want to accelerate beyond these new table stakes.
The Urgency to Adapt
Just as smart phones feel broken when they lack internet access, personal devices will soon feel broken when they don’t leverage AI. This is the future that business leaders must imagine, and anticipate, in the wake of this technology.
| “In no more than 3 years, anything that is not connected to AI will be considered broken or invisible.”
– Microsoft |
AI represents a paradigm shift, not just an incremental improvement. Businesses that embrace this change will have the opportunity to lead their markets, while those that hesitate may find themselves quickly outpaced by more agile competitors.
A McKinsey Global Survey states that 65% of respondents reported that their organizations were regularly using GenAI. This number nearly doubled from a survey conducted 10 months prior. Thus, GenAI adoption is here and increasing at a rapid pace. Organizations, teams, and departments who lag behind will be playing catch up to reach the new normal, rather than accelerating ahead.
To gain a true competitive edge, businesses must look ahead of their skis, so to speak, as GenAI’s capabilities expand. If you could tap into the knowledge of any PhD-level expert, who would you ask? If you could scale up or grow any part of your business with AI, which would it be?
The stakes are clear: leverage AI to stay competitive, or risk being left behind in a rapidly changing market landscape.
Chapter 2: Understanding the Economic Impact on EBITDA
We cannot discuss the effective adoption and scaling of GenAI without acknowledging the economic challenges that limit investments, create risk-averse mindsets, and prioritize cost-cutting. However, we see these challenges as an even stronger justification to explore GenAI in a non-perfunctory, solution-oriented way.
Economic Pressures on Businesses
GenAI arrived in the public eye in the midst of a volatile economic landscape. One of the most concerning forecasts comes from Gartner, predicting that EBITDA margins could shrink by more than 30% by 2027 due to reduced cash flow and rising costs (Source: Gartner Newsroom).
This stark prediction underscores the need for businesses to be proactive in navigating these economic and market challenges, as the implications for long-term profitability and sustainability are significant.
The shrinking of EBITDA margins reflects broader economic challenges, including inflation, supply chain disruptions, and changing consumer behaviors—conditions that have shaped a new normal that business leaders must address.
As these pressures intensify, organizations are contending with both external market forces and internal operational inefficiencies. The traditional strategies of cost-cutting and efficiency optimization may no longer be sufficient to maintain profitability.
| Gartner predicts CFOs will be challenged with EBITDA margins that will shrink by more than 30% by 2027.
– Gartner Newsroom |
The Necessity for Strategic Adaptation: From Cost-Cutting to Value Creation
Given these economic challenges, the need for strategic adaptation is more crucial now than ever.
As mentioned, businesses historically have concentrated heavily on cost-cutting and efficiency gains as the primary strategies to maintain profitability. This approach has often involved refining sales models, reducing general and administrative expenses, and streamlining operations to minimize costs.
GenAI itself can be useful in saving costs, particularly in regards to enhancing productivity and getting more done with less. This is where most organizations start and stop with GenAI: code faster, write faster, produce more iterations of content or design, and leverage intelligent chatbots to curate information.
All of these use cases can serve an organization well, but they will likely not move the needle when it comes to EBITDA margins, at least not in a meaningful, sustained, and measurable way.
Today’s market demands more, especially when competitors are equally well-versed in the simplest applications of GenAI. To start, businesses can approach cost cutting differently. Rather than focusing on the costs of operations, consider the costs of human error. The inefficiencies and mistakes that are common in knowledge work can lead to unexpected increased costs that rise exponentially as customers find them. In turn, mitigating these errors can increase value—by enhancing your final products, retaining customers, attracting new business, and by maintaining efficiency in the entire development process.
This prevention curve demonstrates how AI applied to knowledge work—that is, as a partner, rather than a replacement—can create impactful change and reduce risk.
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A prevention curve that describes the impact of mistakes and when they are found. By applying AI earlier in the prevention curve through tool building in the development phase and risk analysis in the planning phase, AI has had a huge impact on reducing mistakes which in turn drives down costs.
There is an opportunity on the table to create more value with GenAI, but organizations must shift their mindsets to seize it.
Chapter 3: Leveraging Generative AI to Enhance EBITDA
GenAI is a diverse umbrella for a wide array of technologies, and there is no one-size-fits-all answer to create value with this emerging tech. Instead, organizations must consider the new paradigm that GenAI affords them, and apply this thinking to open doors that were previously closed.
Businesses must ask themselves a simple question: How can we improve EBITDA? Now, remove the limits. Do not self-edit due to insufficient resources, time, or expertise. If you applied GenAI productivity gains not to cost-optimization but to revenue generation, what could your team achieve?
KMS Technology has created an AI Quadrant to help business leaders imagine and act upon strategies to create this value with GenAI.
Introduction to the AI Quadrant: A Framework for Applying AI in Market Strategies
This AI Quadrant is a conceptual framework that helps businesses map the potential impact of AI against their market strategies. Based on the Ansoff Matrix, the AI Quadrant is a strategic planning tool that accounts for GenAI as an explosive force for product development with an exponential rather than linear impact.
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Market Development
The Market Development quadrant involves the strategic initiative of selling existing products or services to new markets.
Organizations should ask themselves: How can we scale upstream or downstream to offer our services to previously untapped customer segments?
| Scale upstream | Businesses can utilize AI to deliver products or services to new market segments that demand a higher level of service, a personalized white glove touch. It could involve tailoring existing offerings to meet the specific needs of a more diverse clientele or serving larger clients with more complex requirements. GenAI’s personalization and customization capabilities, paired with its ability to quickly generate more iterations, means businesses can better tailor their pitches and deliverables to previously unreachable prospects and respond faster to client requests. |
| Scale downstream | Open the doors to a greater volume of customers without the same level of resources required. Leverage GenAI to offer self-serve options or support tiers of service at a lower cost. Custom GenAI chatbots can make fantastic customer service agents for self-serve options—but instead of simply cutting costs, a downstream approach allows you to also generate more revenue. |
| Internationalize | GenAI can help businesses cross borders by assisting with translation, region-coding, and customized offerings that appeal to a much broader audience. |
Market Penetration
This quadrant represents selling existing products or services to existing markets more effectively. This involves addressing changing customer preferences and adapting offerings accordingly.
A classic and oft-referenced example is when Blockbuster failed to acknowledge the rapid adoption of the digital experience. Netflix, recognizing the opportunity for digitization and taking it in stride, seized a share of these digitally-destined customers, which ultimately led to Blockbuster’s downfall. Now, in the world of multiple streaming services, AI-driven personalization and custom recommendations have further shifted what consumers expect when they turn on their televisions.
Businesses can lead the market by offering new distribution channels and challenging customer preferences, rather than reacting to the aftereffects of market leaders. With GenAI, businesses can lower the risks of frontiership by applying efficiency gains to innovative tactics. Or, if not the first, be the second—and better—option as consumer behaviors shift.
GenAI allows organizations to both lead and adapt to customers, and reach them in the correct channels more effectively.
Market Diversification
This quadrant involves introducing new products or services to new and existing markets.
Businesses should consider ancillary products and services that can attract new customers or retain existing ones. What happens if you say “yes” when a customer or prospect asks if you can do X, Y, or Z? Could you quickly create an ancillary product, gain immediate feedback, and scale it to market? If you think of GenAI as an accelerator and an enabler of a “what if” idea, you can achieve quick wins without dedicated resources.
Some examples of how AI can enable market diversification include:
- Identifying new growth areas: AI can help businesses identify emerging trends and opportunities for diversification. Predictive analytics are only becoming more powerful, more accurate, and more capable of responding to shifting variables and “what if” scenarios.
- Assessing risks and rewards: Evaluate new ventures’ potential risks and rewards, and pivot quickly in response to real-time data and feedback.
- Developing new capabilities: AI can help businesses acquire the skills and resources needed to succeed in new markets. The next time you wish you had X person on your team, consider how AI can kickstart the role with both generalized and specialized access to knowledge.
In short, AI expands possibilities. It can ensure greater customer retention by fulfilling demands that were previously too complex to fulfill. It can help you take on more business that you would have previously had to turn down. You can start saying “yes”, and exploring different revenue-generating avenues that have previously been inaccessible.
Chapter 4: Roadmapping AI for Strategic Success
AI roadmapping refers to the strategic process of planning and charting the implementation of AI within an organization. Serving as a business guide to navigating the complexities of AI, it involves mapping out the necessary steps, considerations, and timelines to effectively integrate AI capabilities into developing strategies, optimizing existing processes, or building new applications. As businesses seek to leverage AI and machine learning to enhance efficiency and gain a competitive edge, a well-structured roadmap becomes essential to stay focused.
Developing a Strategic AI Roadmap
Think long-term: To develop a successful AI roadmap, companies should take inventory of emerging technologies and ask big questions about how these technologies will impact their industry. Through the roadmapping process, it is important to avoid focusing on the short-term and medium-term. With AI’s exponential growth and the potential impact of this technology, it is key to remember that things are moving faster than you think.
| Technology | Disrupting Questions |
| Super Intelligence | What can you do with a workforce of 1,000 new PhD level consultants? |
| Agent-to-Agent Communication | How would 100% automated B2C and B2B communication change your business? |
| Digital Twins | What is the Google Maps of your industry? |
| Augmented Reality | What happens to your industry when Apple Vision goggles catch on? |
Adopt a holistic approach: integrate corkscrew thinking and think beyond chatbots. Reflect on your organizations’ services, products, and how AI could be applied from the beginning to the end of your development cycle. That means, analyze each step—from conception and brainstorming to delivery, how would additional support and innovation improve the process?
Embrace challenges: Even with known limitations, organizations should make bold assumptions and be confident that the technology will move rapidly to solve these problems. It is easy to see the flaws in GenAI content or images, for example, but businesses should plan for the future state, where AI is producing comparable work—even superior work, in some cases—to humans.
Building the Roadmap
To start your roadmapping journey, consider these variations as a starting point:
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1. Create multiple roadmaps
Companies should develop multiple roadmaps instead of a single one. This approach breaks away from traditional roadmapping because GenAI is more broadly applicable to various aspects of the business. The multi-roadmap approach allows businesses to think more flexibly, explore more productively, and be both realistic and idealistic at the same time. The goal is, again, to think big. Use these buckets to prevent self-editing and truly embrace a wildly different, AI-driven future.
2. Collaborate and prioritize
In the planning phase, organizations should engage in open dialogue between departments, weighing their perspectives. Carefully review each roadmap, selecting those that resonate with the organization’s goals and discarding those that do not align.
3. Converge into a unified roadmap
Ultimately, merge these individual roadmaps into a cohesive, unified strategy that maintains organizational alignment. This final roadmap considers all options and evaluates them against the ultimate goals of your business. In the end, the roadmap should accommodate both the immediate practical adoptions of GenAI and the future advancements or innovative applications of the technology.
By following these steps and maintaining a strategic focus, organizations can effectively navigate the complexities of AI and position themselves for long-term success. Go beyond cost optimization and embrace AI as a means of positively impacting EBITDA margins and creating real value for your business.
Conclusion
Navigating GenAI is not an easy feat.
Many organizations need support from trusted, knowledgeable partners to facilitate conversations that challenge assumptions and visualize a future that can be hard to imagine. Because GenAI evolves so rapidly, it can be extremely difficult for businesses to understand even its current capabilities. You don’t know what you don’t know—thus, look to the experts.
KMS Technology created this GenAI roadmapping approach based on real conversations with customers, investors, and thought-leaders, as well as decades of expertise in AI and ML technologies. Our technologists have been stunned and amazed by the capabilities of GenAI and the speed at which it evolves. We are constantly educating ourselves, testing technologies, adapting as we learn, and building our own solutions.
As a result, we vividly understand the challenges, roadblocks, and hesitations with GenAI adoption, but we equally see the risks of waiting to act.
If you’d like to start a conversation on how to truly realize the gains of GenAI, please contact us.
We’d love to discuss your project!
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