GenAI Use Cases
How to Build a Generative AI Use Case Portfolio
You've taken bold steps in establishing a GenAI Polymath leadership role and familiarizing yourself with the strategic roadmap outlined in the CEO GenAI Playbook. Now, it's time to translate your organization's C-Suite GenAI Agenda into tangible action.
This guide equips you, the senior executive, with a framework for building a robust use case portfolio. By following these actionable steps, you can leverage the expertise of your GenAI Polymath and unlock the transformative potential of Generative AI tools to achieve significant business value.
GenAI Use Case Portfolio Action Plan
Identify Strategic Needs:
Conduct a SWOT analysis: Work with your leadership team to conduct a comprehensive SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis. This analysis will provide a clear picture of your organization's internal capabilities and external environment.
Identify your key strengths that can be leveraged with GenAI, such as a strong data foundation or a culture of innovation. Unearth weaknesses that GenAI could potentially address, such as inefficiencies in product development or repetitive marketing tasks.
Pinpoint significant growth opportunities where GenAI can be a game-changer, and identify potential threats that GenAI can help mitigate, such as disruption from competitors utilizing this technology.
Review existing business challenges and goals: Analyze your current strategic plan and identify specific challenges that are hindering progress toward your goals. For example, if a key objective is to increase customer acquisition, analyze existing marketing campaigns and identify areas for improvement.
Look for areas ripe for innovation: Don't limit yourself to existing challenges. Consider areas within your organization where traditional approaches are reaching their limitations or where disruptive innovation could yield significant benefits.
Brainstorm with your leadership team and the GenAI Polymath to explore how GenAI could revolutionize specific aspects of your business, such as product personalization, supply chain optimization, or risk management.
Match Needs with Generative AI Capabilities:
Research and understand GenAI capabilities: Explore various applications of GenAI tools through industry research, attending conferences and events, or collaborating with your GenAI Polymath.
Gain a solid understanding of how GenAI can be used to create new data (e.g., synthetic data for training AI models), generate creative content (e.g., personalized marketing materials), or automate tasks (e.g., streamline workflows in product development).
Align capabilities with identified needs: Work with your GenAI Polymath to match these platform capabilities with the strategic priorities outlined in Step 1 (identify strategic needs).
For example, if a key need is to improve product development efficiency, explore how GenAI can be used to automate repetitive design tasks or generate new product ideas based on market trends and customer preferences.
Prioritize Your GenAI Use Cases:
Develop evaluation criteria: Establish clear and measurable criteria to evaluate potential GenAI tool use cases. These criteria could include:
Potential impact on business objectives: How significantly can this use case improve a key metric (e.g., sales revenue, customer satisfaction)?
Alignment with overall strategy: Does this use case contribute to achieving your long-term strategic digital business transformation goals?
Feasibility and resource requirements: Can this use case be implemented within a realistic timeframe and budget, considering available resources and expertise?
Ethical considerations: Does this use case raise any potential ethical concerns for your organization, regarding data bias or application fairness?
Prioritize based on the evaluation: Rank potential use cases based on the defined criteria. Focus on those with the highest potential impact, alignment, and feasibility. Your GenAI Polymath can provide valuable insights into the technical merit and resource requirements for each use case.
Develop an Implementation Action Plan:
Develop a timeline for each use case: Establish realistic timelines for each prioritized use case, considering the development, testing, and deployment phases. Work with your GenAI Polymath to create a phased approach that allows for iterative development and learning.
Allocate resources: Identify the necessary resources for each GenAI use case. This could include personnel with expertise in data science, software development, and the specific business domain. Depending on the complexity of the use case, you may need to allocate additional resources for data acquisition, infrastructure, or external consultants.
Define success metrics: Establish key performance indicators (KPIs) to track the progress and success of each GenAI use case implementation. These metrics should be directly tied to the business objectives outlined in Step 1 (identify strategic needs).
For example, if a GenAI use case aims to improve customer acquisition, a key metric could be the conversion rate from website visitors to paying customers.
Establish a governance framework: Develop a framework for overseeing the development and implementation of GenAI use cases. This framework should address data governance, ethical considerations, and risks to the organization.
Conclusion and Next Steps
By establishing a GenAI Polymath role, and by following this series of proven guidance, you've laid the foundation for leveraging Generative AI effectively. This guide has equipped you with the knowledge and framework to build a strategic Generative AI use case portfolio.
Now, it's time to collaborate with your GenAI Polymath to translate these use cases into reality. Through a collaborative effort, you can leverage the power of Generative AI to address key business challenges, unlock new application opportunities, and drive significant and sustainable growth for your organization.
If you need additional industry domain-specific guidance, review our GenAI Research.
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