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Strategic Alignment in the GenAI Era: Guiding the Executive Committee for Success

February 2024

Artificial intelligence (AI) is a broad category of technologies capable of mimicking human intelligence or performing complex tasks. Presently, however, the specific field of generative AI (GenAI) and large language models (LLMs) seems to have captured our collective attention due to its ability to convincingly replicate the most human of activities, language. Although the true extent of GenAI’s potential is still hard to predict, and its potential risk factors are vast, our fascination with the technology is already leading to significant investments and its momentum shows no signs of slowing as companies succumb to the fear of being left behind in a paradigm shift.

The consequences of watching from the sidelines as GenAI innovations unfold are potentially severe for boards and executives, very few of whom have established an agreed upon strategic intent for GenAI, despite underwriting large investments. Consider the tumultuous saga surrounding Sam Altman’s recent departure and subsequent reinstatement as CEO of OpenAI — not even the leaders of the companies developing these technologies are aligned around how they should be nurtured and governed. This clearly underscores the criticality of ethical, technically savvy contributors in the executive leadership team and boardroom, as well as the need for companies to evolve some of their key technical domains and leadership positions to ensure sound ownership of these issues. As we look to the years ahead, we see significant implications for leaders at all levels of the organization:

  • GenAI is not just a technological evolution; it’s a strategic shift that demands a comprehensive understanding and alignment across executive levels.
  • Executive committees must grasp the intricacies of AI and be fully aligned with its potential applications to effectively shape and implement GenAI strategies.

As they build their knowledge base, CEOs and the broader executive team should understand the key technology stakeholders in developing and implementing AI strategy. These include:

  • Chief data officer (CDO)
  • Chief technology officer (CTO)
  • Chief analytics officer (CAO)
  • Chief digital officer (CDO)
  • Chief information officer (CIO)
  • Chief artificial intelligence officer (CAIO)

While the approach companies take will vary depending on the technology roles they have in place and how they are structured, each of these leaders brings a unique perspective about the opportunities AI presents and the organization’s readiness for transformation. Together, they play a pivotal role in shaping and executing GenAI strategies.

The quality and quantity of data are the lifeblood of AI, and CDOs are the custodians of this invaluable resource. Collaborating with CIOs and CTOs, CDOs ensure not only the efficiency of data management but also its role as the fuel for GenAI, facilitating learning and improvement.


In overseeing data assets, chief data officers encounter the formidable task of guaranteeing both the quality and quantity of data. The complexity of sustaining an efficient and effective data ecosystem — encompassing aspects like security and compliance, coupled with the responsibility of providing essential content for AI systems — demand close collaboration with IT leadership. The challenges extend to establishing a data-driven culture and ensuring scalability and future-readiness, collectively presenting substantial hurdles.

Foundation for success

Success involves crafting a robust data strategy, fostering a data-led culture, implementing proper governance, and establishing fruitful partnerships with executive technology leaders such as the CIO and CTO. These elements collectively empower CDOs to drive innovation and cultivate growth within organizations, particularly in the dynamic landscape of GenAI.

The chief digital officer role is less common today, as many organizations have integrated its responsibilities into CIO or CTO strategies, with a focus on embedding GenAI into digital technologies. Where it exists, the chief digital officer role is pivotal in automating tasks, enhancing efficiency and birthing new products and services.


Chief digital officers grapple with a range of challenges in the evolving landscape of digital transformation, particularly in integrating GenAI. This includes seamlessly integrating GenAI into existing digital technologies, automating tasks for efficiency, creating new products and services, balancing investments, ensuring data privacy and security, and navigating evolving customer expectations.

Foundation for success

Achieving success involves possessing a comprehensive understanding of the relevance of digital technologies to strategic decisions and cultivating effective collaboration skills. This combination empowers individuals to drive innovation and foster growth within organizations, especially in the dynamic landscape of GenAI.

The product management landscape is constantly evolving, and in recent years a significant paradigm shift has emerged. This shift revolves around moving away from traditional, project-centric approaches and embracing a more customer-centric, data and tech-driven, and iterative way of building and managing products. In this shift, CTOs play a pivotal role; their responsibilities encompass identifying and evaluating GenAI technologies, collaborating closely with the chief product officer (CPO) to advance product lifecycle management and shaping the organizational technology roadmap. CTOs are at the forefront of integrating GenAI into the product development process, balancing innovation with practical implementation, and uplifting the organization’s technology assets to ensure adaptability and alignment with the evolving technological landscape. Their strategic vision and collaborative efforts contribute significantly to the organization’s success in navigating and imbedding GenAI.


CTOs need to develop and deploy GenAI solutions, while navigating the shifting paradigm in product management. They must balance technological advancements with strategic objectives, collaborating closely with the chief product officer to shape the product roadmap while enhancing the organization’s technology assets.

Foundation for success

To succeed in the GenAI era, CTOs should integrate AI across operations and the product life cycle, invest in skill development, adopt agile practices, focus on scalability, cultivate innovation, stay regulatory-compliant, adopt a customer-centric approach and monitor industry trends.

Ensuring a robust and secure technology stack, CIOs lay the groundwork for AI initiatives. From developing governance and resource allocation frameworks to fostering innovation, CIOs are instrumental in the successful development and implementation of GenAI.


Chief information officers face numerous challenges in navigating the adoption of GenAI. These challenges include ensuring a robust and secure technology foundation, developing ethical governance frameworks, making strategic decisions on resource allocation and build-versus-buy dilemmas, fostering a culture of innovation, addressing talent acquisition and development, seamlessly integrating GenAI with existing systems, prioritizing data privacy and security, and aligning AI initiatives with broader organizational strategies.

Foundation for success

CIOs establish a secure technology foundation by adopting a business mindset when articulating resource needs for technological investments. Effective talent management ensures a top-tier IT organization aligned with AI initiatives and organizational strategies. Prioritizing ethical governance, fostering innovation, and emphasizing data privacy are essential for organizational competitiveness and thriving in the evolving GenAI landscape.

Tasked with using data and analytics to drive decision-making, CAOs leverage GenAI to identify business problems and develop data-driven strategies. This involves analyzing patterns, enhancing reporting and establishing feedback loops for continuous improvement.


CAOs need to ensure continuous refinement of AI systems, collaborate closely with business intelligence teams, strategically align GenAI initiatives with broader organizational goals and establish analytics that yield actionable insights.

Foundation for success

To overcome challenges, CAOs need a comprehensive grasp of analytics and AI, translating both customer-centric and product-centric business needs into data-driven solutions. Staying updated on technological advancements is crucial in the GenAI era, where continuous adaptation in response to emerging trends is a differentiator. Key strategies include data-driven product development, customer segmentation, personalization, optimization of pricing and supply chain strategies, performance monitoring, risk management and collaboration with product teams.

Responsible for developing and implementing AI strategies ethically, CAIOs oversee the design and deployment of advanced algorithms crucial for GenAI systems to process, understand data and make informed decisions.


Beneath the surface of GenAI outputs lurks a potential pitfall: bias. Generative AI, like any system trained on human-generated data, can unintentionally inherit and amplify biases present in that data. This challenge is compounded by datasets containing inaccuracies and models trained on historical inequalities. Chief artificial intelligence officers grapple with these crucial challenges while steering the development and implementation of AI strategies. These responsibilities encompass ensuring ethical and responsible use of AI, overseeing the design and deployment of advanced algorithms, aligning AI strategies with organizational goals, balancing innovation with ethical considerations, staying ahead of technological trends, fostering a culture of responsible AI, and building and maintaining customer and stakeholder trust.

Foundation for success

To achieve success in addressing these challenges, CAIOs need to collaborate with the full executive committee to streamline the advancement of GenAI. Navigating the technical and ethical dimensions of AI, CAIOs play a crucial role in advocating for responsible practices. The success of AI initiatives also depends on how well they align organizational values.

Scoping the opportunity: How companies across sectors are using GenAI today

In various industries, organizations are leveraging GenAI to foster innovation and improve operational efficiency. Below are examples of companies from five distinct sectors that persistently drive the adoption of GenAI, propelling not only their businesses but also the broader industry forward.

  • Retail: Walmart employs GenAI to elevate its search functionality, delivering more relevant results and personalized recommendations to customers. The retailer is also delving into GenAI applications for optimizing pricing strategies, utilizing data analysis to determine optimal prices and maximize revenue.
  • SaaS: Salesforce integrates GenAI, particularly Einstein GPT, into its cloud-based CRM platform. This GenAI-powered language model generates personalized content, such as sales pitches and product descriptions, enabling sales representatives to focus on relationship-building. Salesforce views GenAI as transformative, revolutionizing its CRM platform and enhancing customer interactions.
  • Industrials: Honeywell, a control system company, leverages GenAI to automate tasks and streamline processes. This includes deploying GenAI in plant operations to assist technicians and operators, reducing crew requirements, and enhancing efficiency. Honeywell also utilizes GenAI to optimize supply chains by predicting demand, managing inventory and scheduling deliveries.
  • Financial services: Morgan Stanley utilizes GenAI to enhance investment research, improve customer service and innovate financial products. GenAI facilitates the analysis of large datasets to uncover patterns and trends imperceptible to human analysts. Morgan Stanley also employs GenAI to personalize investment portfolios for clients and develop new financial products like index funds and ETFs.
  • Healthcare and life sciences: In healthcare, Novant Health employs GenAI to create chatbots and virtual assistants. These tools aid patients by addressing health-related queries, tracking moods and symptoms, and identifying potential triggers for mental health conditions. GenAI enhances patient engagement and supports mental health monitoring in the healthcare sector.

Building an organization that supports GenAI innovation

Success in the GenAI era hinges on the collaboration of cross-functional teams, bringing together experts from diverse technology and business domains. The goal is not to replace human intelligence but to synergistically augment it with GenAI. Embracing GenAI is not merely an option for leaders; it has become a strategic imperative for organizations aiming to thrive in this era of profound technological transformation.

Recognizing the transformative potential of AI and fostering collaboration across disciplines are pivotal components of a strategic approach for organizations navigating the complexities of the technological landscape. Key to success is recognizing the important roles executives across the company play in defining the specific opportunities for the business and collaborating effectively to make them a reality. Clear communication, shared objectives and collective responsibility are paramount in the realms of digital, product and technological transformation. By taking these steps, businesses can ensure that they are well-positioned to capitalize on the strategic implications of GenAI.

CEOs and the broader executive committee can foster an environment that encourages these behaviors by educating themselves on GenAI, bringing together the right team of business and technology leaders to develop a GenAI strategy that aligns with the organization’s overall goals and objectives, investing in GenAI training and development for employees, and fostering a culture of innovation and experimentation.

Planning for GenAI transformation: The questions CEOs should be asking

  • Do we have a robust GenAI strategy that aligns with our overall strategy and objectives?
    • Do we have the analysis we need to shape strategy?
    • What’s the level of urgency? What’s the time frame we’re working in?
    • Which functions are most impacted by business model shift?
    • Do existing functions and business units have a game plan for the GenAI impact we have identified?
  • Do we have the right resources?
    • Are the people in key technology and business leadership roles prepared and able to develop strategy and make the necessary operational changes?
    • Are we able to shift the focus of existing people, investments and agendas, or do we need new capabilities, higher levels of investment?
    • Do we know how to assess for the capabilities we need?
    • Do we know how to find the talent we need?
    • What leadership development and training do we need?
    • Are we working effectively across functions and business units to collaborate on GenAI opportunities and priorities?
  • What are our legacy challenges?
    • Are our business processes and systems getting in the way of the changes we need to make?
    • What facets of our culture need to be evolved?
    • Are information, functional or business silos likely to be hurdles?
    • Do we have an incentive structure that promotes collaboration?
    • Are our information processes and systems compatible with each other and the technologies enabling digital?
    • Do we have a culture, benefits, etc. to attract and retain top talent?

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