Generative AI (GenAI) has emerged as a transformative force across industries. However, with this potential comes significant challenges, particularly for CEOs and CFOs tasked with managing costs and demonstrating return on investment.
Based on insights from a recent webinar by Gartner featuring AI economics expert Nate Suda, Senior Director Analyst at Gartner, Benjamin Seesel, VP of advisory at Gartner, and Clement Christensen, Senior Director Analyst at Gartner, this guide aims to provide a strategic framework for unlocking GenAI's potential by aligning expectations on value and cost.
What are the Challenges for CFOs and Organizations in Unlocking the Potential of GenAI?
GenAI has rapidly risen to prominence in board-level discussions. It has even surpassed cloud computing and digital transformation in strategic importance. For CFOs, this shift presents a unique set of challenges:
Pressure for ROI justification: With the era of cheap cash ending, CFOs face increasing pressure to justify every dollar invested in GenAI. The board and stakeholders are demanding clear evidence of returns, putting CFOs in the spotlight to demonstrate the value of these often substantial investments.
Uncertainty in ROI calculations: Unlike more established technologies, GenAI's potential returns are often speculative and difficult to quantify. This uncertainty makes traditional ROI calculations challenging and potentially unreliable.
Balancing innovation with fiscal responsibility: CFOs must balance innovation and maintaining financial discipline. CFOs face a delicate balancing act. They must weigh the fear of missing out on GenAI's potential against the need for prudent economic management.
Lack of established benchmarks: GenAI is a relatively new technology, so industry benchmarks or best practices for financial planning and performance measurement are scarce.
Talent and resource allocation: It's challenging to determine the appropriate level of investment in GenAI talent and infrastructure. This is especially true when GenAI competes with other strategic initiatives for limited resources.
What are the Critical Cost Dynamics of GenAI that Organizations Need to Understand?
Understanding and managing the cost dynamics of GenAI is crucial for its successful implementation. The webinar experts highlighted several key factors:
Significant cost overruns: Over half of organizations abandon their GenAI efforts due to miscalculated potential costs. Alarmingly, cost overruns of 500% to 1,000% are not uncommon in GenAI projects.
User behavior impact: A major factor contributing to these overruns is the underestimation of user behavior, particularly regarding how frequently they interact with GenAI tools. The cost model for many GenAI applications is based on usage, similar to being charged per word in a meeting, which can lead to unexpected expenses as adoption increases.
API usage costs: Organizations must carefully consider the cost implications of API usage. Many GenAI tools differ from traditional software with fixed licensing costs. Instead, they charge based on interaction volume. This can lead to quickly escalating costs as adoption becomes widespread.
Data preparation costs: The expenses associated with data cleansing and preparation are often underestimated. In some cases, these costs can far exceed the actual implementation costs of the GenAI solution.
Ongoing operational costs: Beyond initial implementation, the ongoing costs of running, maintaining, and scaling GenAI systems can be substantial and are often overlooked in initial budgeting.
Hidden costs of experimentation: Many organizations fail to account for the costs associated with experimentation and failed initiatives, which are often necessary to find the right GenAI applications for their business.
How are CFOs Responding to the Financial Risks and Uncertainties around GenAI Investments?
In response to these challenges, CFOs are adopting more sophisticated and flexible approaches to managing GenAI investments:
Shift to proof-of-concept funding models: CFOs are moving away from traditional net present value (NPV) calculations and are increasingly adopting proof-of-concept funding models. These models incorporate stage gates based on value-aligned metrics, allowing for more flexibility and de-risking of investments while maintaining control over the business case.
Focus on operational indicators: In the early stages of GenAI adoption, CFOs are shifting focus. Instead of relying solely on financial metrics, they look at operational indicators, which often precede financial returns. This approach allows a more nuanced understanding of the technology's impact and potential.
Portfolio approach to investments: CFOs are beginning to manage GenAI investments as a portfolio, balancing high-risk, high-reward projects with more conservative initiatives to spread risk and maximize potential returns.
Collaboration with IT and business units: CFOs are recognizing the complexity of GenAI and are working more closely with IT departments and business units to better understand the technology and its potential applications.
Emphasis on value harvesting: There's a growing focus on having clear plans for converting productivity gains from GenAI into tangible value, whether through revenue growth or cost savings.
Adaptive budgeting processes: Some CFOs are implementing more flexible budgeting processes that allow for rapid resource reallocation based on the results of GenAI experiments and pilots.
What are the Different Business Case Patterns for GenAI, and How Do They Differ in Cost and Value?
The experts outlined three main business case patterns for GenAI, each with distinct cost dynamics, value propositions, and ROI expectations:
Defend
Focus: Competitive parity and individual productivity
Cost range: Approximately $500 per year per worker
Value proposition: Improves employee productivity and satisfaction but may not directly impact top or bottom line
ROI expectation: Often marginal in financial terms, but can significantly improve employee Net Promoter Score and retention
Example: Implementing AI-powered productivity tools like Copilot
Extend
Focus: Enhancing existing processes for differentiation
Cost range: Starting at about $2 million
Value proposition: This can lead to significant improvements in specific business processes.
ROI expectation: Typically sees a 2:1 to 4:1 benefit-to-cost ratio
Example: Using GenAI to improve customer service response times and quality
Upend
Focus: Radically reshaping business models
Cost range: $20 million to nearly $1 billion
Value proposition: Potential to transform the industry and create entirely new revenue streams
ROI expectation: High risk, but the potential for returns as high as 100:1
Example: Using GenAI for drug discovery in pharmaceuticals
Organizations must align their GenAI initiatives with the appropriate pattern to set realistic expectations and accurately measure success. It's crucial to understand that these patterns are not necessarily sequential stages but rather different approaches that can coexist within an organization's GenAI strategy.
How can Organizations Build a Strong Business Case for GenAI Investments?
Building a compelling business case for GenAI investments is complex. It requires a nuanced approach that goes beyond traditional ROI calculations. Consider the following strategies:
Align value statements with technology: Clearly articulate how the GenAI initiative supports broader business objectives and strategy.
Tailor metrics to the business case pattern:
For "defend" initiatives: Focus on return on employee (ROE) metrics like employee satisfaction, productivity perception, and reduced turnover.
For "extend" initiatives: Use established KPIs such as ticket resolution time, customer satisfaction scores, or process efficiency improvements.
For "upend" initiatives: Develop long-term value metrics that capture the potential for industry transformation and new revenue streams.
Quantify the problem: Start by defining and quantifying the business problem or opportunity that GenAI aims to address. This provides a baseline for measuring impact.
Stage-gate approach: Implement a stage-gate funding process. In this approach, additional investment is tied to specific achievements. These may include reaching certain milestones or proving key hypotheses.
Consider indirect benefits: Factor in indirect benefits such as improved decision-making quality, faster time-to-market, or enhanced innovation capabilities.
Risk-adjusted returns: Incorporate risk assessments into the business case, acknowledging the uncertainties associated with GenAI implementations.
Scenario planning: Develop multiple scenarios to account for different levels of success and adoption rates, providing a more realistic range of potential outcomes.
How can organizations maximize productivity gains with GenAI?
Maximizing productivity gains from GenAI requires a holistic understanding of how the technology can impact various aspects of work:
- Speed: While GenAI can accelerate task completion, it's important to ensure that faster doesn't come at the expense of quality or strategic thinking
- Quality of prioritization: GenAI can help employees focus on high-value tasks by automating or streamlining lower-value activities
- Alignment of work: GenAI can optimize workflows through improved coordination and information flow. This optimization can occur even if individual tasks don't become faster
- Impact and effectiveness: For knowledge workers, GenAI can enhance the quality and creativity of outputs, leading to more impactful work
- Contextual deployment: Use the "zone of deep productivity" matrix to identify workers likely to benefit most from GenAI. This assessment is based on the worker's experience level and the complexity of their function
- Training and change management: Invest in comprehensive training programs to ensure employees can effectively leverage GenAI tools daily
- Continuous improvement: Regularly gather feedback and monitor usage patterns to refine and optimize GenAI implementations
How can Organizations Identify the Use Cases that Truly Deliver Value from GenAI?
Identifying high-value use cases for GenAI requires a strategic approach:
- Focus on unique capabilities: Prioritize areas where GenAI offers capabilities other technologies cannot match
- Assess the full value chain: Consider GenAI as part of a broader solution chain rather than a standalone fix
- Align with strategic objectives: Ensure GenAI initiatives directly support key business goals and strategies
- Start with well-defined processes: Look for opportunities in areas with transparent, existing processes and KPIs to measure impact more easily
- Consider data readiness: Evaluate the availability and quality of data required for effective GenAI implementation
- Balance quick wins and transformative projects: Aim for easily achievable, short-term gains and more ambitious, long-term initiatives
- Cross-functional collaboration: Involve diverse stakeholders to identify use cases that may not be apparent from a single departmental perspective
How should Organizations Approach Budgeting and Portfolio Management for their GenAI Investments?
Effective budgeting and portfolio management for GenAI investments requires a strategic and flexible approach:
- Portfolio approach: Balance investments across defend, extend, and upend categories to manage risk and potential returns
- Align with strategic pillars: Ensure GenAI investments support the organization's core strategic objectives
- Flexible allocation: Be prepared to reallocate funding based on experimentation results and changing priorities
- Staged funding: Implement a staged funding approach, starting with smaller investments for proofs of concept before committing to larger-scale implementations
- Risk-adjusted budgeting: Allocate budgets based on the risk profile of different GenAI initiatives, with higher-risk projects potentially receiving smaller initial investments
- Continuous evaluation: Regularly review the GenAI portfolio to assess performance and make necessary adjustments
- Talent investment: Include budget allocations for acquiring and developing talent to support GenAI initiatives
- Infrastructure considerations: Factor in the costs of upgrading or adapting existing IT infrastructure to support GenAI implementations
Conclusion
Unlocking GenAI's potential requires a strategic, multifaceted approach that balances innovation with financial prudence. CEOs and CFOs must work together to create a culture that embraces experimentation while maintaining financial discipline.
Organizations can navigate the challenges and uncertainties surrounding GenAI by:
- Understanding different business case patterns
- Aligning initiatives with strategic goals
- Adopting a portfolio approach to investments
The journey to realizing value from GenAI is likely to be complex and, at times, unpredictable. However, by applying the insights and strategies outlined in this guide, organizations can position themselves to capitalize on GenAI's transformative potential while effectively managing the associated risks and costs.
Long-term success in the evolving GenAI landscape will depend on several factors:
- Maintaining flexibility
- Enabling continuous learning
- Staying attuned to emerging best practices
Want to explore how GenAI tools like Alltius can help CFOs?
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