Navigating the gen AI revolution: Insights from industry leaders
June 27, 2024 / Mike Thomson
Short on time? Read the key takeaways:
- Aligning generative AI initiatives with specific business outcomes is crucial for success, ensuring that AI investments drive meaningful results aligned with strategic goals.
- Traditional ROI metrics alone may not fully capture the value of generative AI; a more comprehensive approach considering qualitative factors and long-term benefits is needed to evaluate AI investments accurately.
- Cultivating an AI-ready culture centered on experimentation, continuous learning, adaptability, and empowering employee education is essential to capitalize on generative AI's transformative potential.
- Proactively addressing risks and ethical considerations like data privacy, algorithmic bias, and potential misuse through robust principles, governance, and stakeholder engagement is vital for responsible, trustworthy AI deployment.
The role of a business leader is to navigate the ever-shifting landscape of our industries and chart a course toward success. Today, one of the most promising navigational tools is generative AI.
I recently joined other business leaders at two events organized by Unisys and Harvard Business Review Analytic Services in New York City and London. These gatherings brought together experts from technology and business to explore the potential of generative AI and share insights on how organizations can leverage its power to drive innovation, efficiency and growth.
During the events, common themes highlighted the importance of embracing AI while navigating its challenges and opportunities. Here's a summary of the topics I believe you'll find valuable as you consider your organization's approach to generative AI.
Aligning AI with business objectives
Our discussions repeatedly emphasized the crucial role of aligning generative AI initiatives with well-defined business objectives. While it's easy to get caught up in the hype around AI, success depends on aligning AI investments with the organization's strategic goals. To achieve this, it's essential to clearly articulate the desired business outcomes and the specific problems you aim to solve.
Too often, companies get so focused on technology that they lose sight of the value they're trying to create. By concentrating on concrete business objectives from the outset, organizations can avoid this pitfall and ensure that their AI efforts are both technologically impressive and drive meaningful results.
Rethinking success metrics
Because of its emerging nature, traditional ROI metrics may not fully capture the value of generative AI initiatives. Given the technology's potential for growth and impact, organizations need to reassess how they measure success.
Quantifiable elements are essential, but it's also crucial to consider qualitative factors and the long-term benefits that may not be immediately apparent. Adopting a more comprehensive approach to evaluating AI investments can help businesses make informed decisions that position them for long-term success.
Cultivating an AI-ready culture
Fostering an organizational culture primed for AI adoption surfaced as a key theme, encouraging experimentation, continuous learning, and adaptability. This cultural shift starts with leadership setting the tone and providing the necessary support and resources for teams to embrace AI-driven innovation.
By cultivating an environment that values exploration and learning, organizations can empower their employees to drive meaningful change. Investing in ongoing education and employee development is part of this cultural shift. As AI technologies advance, organizations must equip their workforce with the knowledge and skills to utilize them effectively.
Addressing risks and ethical considerations
While generative AI is powerful, proactively addressing risks and ethical concerns like data privacy, bias, and misuse is critical. Companies need robust frameworks and principles for responsible deployment, with ethical AI values embedded throughout the lifecycle. This requires ongoing employee training, auditing and strong governance.
Transparency and open stakeholder dialogue also foster trust as AI evolves. Engaging customers, regulators, and the public in addressing concerns maintains accountability. Prioritizing ethics and transparency from the start allows businesses to navigate AI's complexities confidently while mitigating risks and ensuring trustworthy adoption.
Getting started with generative AI
Our exploration also addressed practical steps organizations can take to embark on their generative AI journey responsibly and effectively. Because the total cost picture is uncertain at the outset, getting started the right way is crucial.
- First, start with a cloud foundation that allows for experimentation. This provides the flexibility and scalability to explore and test various AI use cases.
- Next, organizations should select targeted use cases with potentially high ROI. Companies can maximize the value of their AI investments by focusing on specific applications that align with business objectives.
- Conducting pilots and assessing the results is another critical step. This allows organizations to validate the potential of generative AI in a controlled environment and make data-driven decisions about further implementation.
- Importantly, ethical considerations should be integrated from the very beginning. When selecting use cases and conducting pilots, organizations should carefully evaluate the potential risks and impacts on data privacy, algorithmic bias, and other ethical concerns. Establishing clear ethical principles and guidelines during these early stages can help mitigate issues down the line.
- Finally, leveraging partnerships can provide valuable experiential knowledge. By collaborating with organizations with expertise in generative AI, companies can accelerate their learning, avoid common pitfalls, and gain insights into best practices for responsible AI deployment.
The path forward
Generative AI is poised to reshape the business world as we know it. The discussions at the Unisys-HBR events underscored the importance of a holistic approach that combines technological expertise with a deep understanding of business objectives, a commitment to continuous learning, and a dedication to responsible innovation.
For a closer look at how organizations are applying generative AI and the challenges they face, the recent report from Harvard Business Review Analytic Services, sponsored by Unisys, is a great resource. The report, titled "Operationalizing Generative AI for Better Business Outcomes," explores the state of gen AI adoption across 500 leading organizations and provides valuable insights into realizing real ROI from gen AI investments. Here are some key highlights:
- 73% of respondents expect gen AI to be valuable to their organization
- 76% are using, piloting, or exploring gen AI for business purposes
- However, only 41% are realizing a positive ROI from using gen AI
By understanding these trends and learning from the experiences of others, you can make more informed decisions about your gen AI initiatives and navigate the path forward with greater confidence.
