For firms backed by public equity, implementing artificial intelligence (AI) isn’t just a trend—it’s a way to accelerate operational efficiencies and unlock new growth through AI-powered products and services. With global investment in generative AI rising from $3 billion in 2022 to $25 billion in 2023 according to Deloitte – and expected to continue to rise – now is the time to explore how the right AI leadership could drive your company’s success.
However, the choice of an AI leader isn’t just about filling a role—it’s about finding someone who aligns with your company’s strategic goals, data maturity, and operational nuances. Each of these factors influences the specific expertise, vision, and approach needed for a leader to drive measurable impact and bottom-line EBITDA. Selecting the right fit demands a nuanced understanding of both your company’s current capabilities and the competitive landscape. Here’s how to start.
Two AI Strategy Approaches for Growth-Stage Companies
When thinking about AI strategy for a growth-stage company, there are two primary paths:
Operational Efficiency
Many growth-stage companies begin their AI journey to boost operational efficiency, focusing on automating large portions of manual and repetitive tasks like language translation, price forecasting, or streamlining customer service processes. However, the goal is often not full automation of a workflow; instead, it’s about targeted improvements—such as reducing average customer service call times by 10% or halving the hours spent preparing for a claims review. This strategic approach to AI typically offers a more predictable ROI and often lays the groundwork for future product development.
New Product Development
Beyond operational efficiencies, AI can fuel the creation of new, data-driven products and services. By harnessing proprietary data and unique insights, companies can unlock fresh revenue streams and build a sustainable competitive edge. An equally compelling middle step is reimagining the delivery of an existing service or product line. For example, can we bring this product to market with a 4-day SLA instead of 2 weeks? Can we respond to a customer request in 1 hour instead of 5 days? This approach not only improves service but also enhances agility and customer satisfaction.
7 Key Questions to Identify Your Ideal AI Leader
To find the right AI executive, here are essential questions that can help clarify your company’s priorities:
What is our primary goal for implementing AI?
Identifying whether your focus is operational efficiency or developing new AI-driven products will help target the specific type of AI executive you need.
What is the status of our data strategy?
Data maturity plays a critical role in your AI capabilities. Is your data structured, organized, and accessible? If not, an AI leader skilled in data strategy and data management could be essential to optimize and prepare your data for AI. If this is the first time your organization is making a serious investment into the company’s data strategy, stakeholder management and transformation capabilities will likely be highly valued.
How integrated is software in our current service delivery?
If your business model is primarily software-driven, an AI product leader who can innovate with AI may be needed. For more traditional service models, AI leadership focused on digital transformation might be a better fit.
What are our ROI expectations for AI initiatives, and how quickly?
If immediate ROI is the priority, consider AI leadership focused on operational efficiencies and cost savings. This often emphasizes a “buy over build” strategy to accelerate proof of concept and quickly assess value. For organizations with a longer-term vision, an AI product development leader can be instrumental in driving future-oriented growth.
What business processes could benefit most from AI-driven automation?
Identifying specific, repetitive tasks that would benefit from AI automation can help narrow down your search to leaders skilled in operational AI applications, particularly in process automation and workflow optimization.
Do we have proprietary data that could fuel new AI-driven services or products?
Proprietary data offers immense potential value. An experienced AI leader can help your company leverage this data to unlock new revenue streams, improve customer experience, or drive data-driven product development.
Would a hybrid AI leader with engineering and product management skills add value?
Many growth-stage companies benefit from hybrid leaders who combine technical engineering expertise with product development skills. This versatility is ideal for firms evolving from operational efficiencies toward new AI-driven products.
For growth-stage companies, selecting the right AI leader is a strategic decision that impacts immediate efficiency and future innovation. Start by aligning the leader’s skills with your company’s current data maturity and core goals, whether in operational efficiency or product development. Hybrid leaders, who can adapt as your AI needs evolve, may offer significant long-term value by bridging immediate and future-oriented AI strategies. With a clear roadmap and the right leadership, your company can fully leverage AI’s potential to drive efficiency, develop new offerings, and build a sustainable competitive edge.
Kyle Langworthy is Head of Head of AI, ML, and Data Practice at Riviera Partners. Connect with him on LinkedIn.
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