Should your organization start an AI task force?
The surge in interest surrounding generative AI has sparked the formation of AI task forces across various sectors. Contrary to fears of AI replacing human labor, McKinsey views generative AI as an empowering tool for the workforce. Their recent forecast suggests that by 2030, generative AI could inject trillions into the global economy by automating around 70% of business activities across diverse occupations.
In alignment with McKinsey’s perspective, organizations like Disney and the US government are establishing generative AI task forces. Their rationale is clear: recognizing the significance of this technology for both present and future operations, they seek to unlock its potential effectively.
Put simply, many business leaders are grappling with how to navigate this transformative technology and are assembling expert teams to chart a course forward — hence, the emergence of generative AI task forces.
An increase in generative AI task forces
A generative AI task force serves as a multidisciplinary team assembled to explore the potential of AI in driving innovation, enhancing product quality, and bolstering competitiveness within an evolving business landscape. Their objective is to enable organizations to harness the benefits of AI technology while navigating associated risks and challenges in software development and security. This encompasses establishing ethical guidelines for AI usage both internally and externally, as well as optimizing workforce capabilities to maximize business impact.
Having been deeply entrenched in the AI industry for the past decade, Veritone has gained valuable insights into best practices for organizations considering the integration of AI. Here are some key considerations to guide your task force as you embark on this journey.
How to start a generative AI task force
To kickstart your generative AI journey, it’s imperative to assemble a team with deep expertise in the specific type of AI you intend to implement. This ensures informed decision-making tailored to your product or business case.
Begin by juxtaposing your current processes with the potential adoption of AI. This comparative analysis is crucial for understanding the technology’s capabilities, implementation costs, and associated trade-offs.
Every task force requires a solid foundation to guide its approach. Start by probing your current technology infrastructure with key questions:
– What are the organization’s current challenges?
– What outcomes are desired?
– What types of value are prioritized and how can they be achieved?
Using the answers to these questions, establish clear short- and long-term objectives aligned with the overarching business goals, ensuring stakeholder buy-in. With these objectives in mind, select a pilot project. Opting for a manageable project that delivers tangible benefits in the short term is essential for long-term success.
For example, a Veritone customer began by integrating generative AI into their customer support processes. They opted for automated responses, providing a selection of support sessions that could be adjusted as necessary. This pilot project effectively demonstrated the concept’s efficacy without overwhelming resources.
Following successful validation, companies can expand their generative AI initiatives by identifying other areas of the business poised to benefit from the technology. An iterative approach, involving testing, learning, and refinement, will yield superior results and ensure the development of a robust framework for the future.
Best practices
To ensure your team navigates generative AI effectively, consider these best practices:
- Continuous training and learning: Invest in ongoing training and resources to keep your team on top of the latest AI tech, skills, and knowledge.
- Collaboration and feedback loop: Establish regular check-ins with all stakeholders and establish a feedback process to facilitate continuous refinement throughout the project lifecycle.
- Scalability and maintenance: Develop strategies for scalability, consistent maintenance, and updates to construct a resilient AI framework that can adapt to changing needs over time.
- Performance metrics: Define key performance indicators (KPIs) and benchmarks tailored to each project to measure success and track progress.
- Ethical considerations: Prioritize transparency, data privacy, and bias prevention in AI models, value helping and enhancing the workforce rather than replacing it, and establish ethical standards for the responsible use of AI internally and externally.
- Feasibility study: Conduct a comprehensive assessment of AI feasibility, evaluating technological infrastructure, and assessing financial implications to inform decision-making and project planning.
- Realistic expectations: The team and stakeholders should have a clear understanding of generative AI’s capabilities — overestimating its capabilities can prolong development timelines and potentially lead to dissatisfaction among end-users.
What can AI do for your business?
AI adoption is not one-size-fits-all; each organization must tailor its approach to suit its unique needs. This involves assembling the right team, implementing systems that yield tangible results, and fostering accountability to maximize return on investment (ROI). Seasoned experts in AI can provide valuable insights and accelerate the adoption process, helping organizations either catch up or leap ahead of their competition.
Veritone has a wealth of experience supporting clients across diverse sectors for nearly a decade, including recent collaborations with the federal government to implement innovative AI solutions. The sooner an organization grasps the implications of AI for its operations, the better positioned it will be for success in an increasingly competitive landscape.
Download the free AI task force guide to learn more.