Podcast Summary
Five simple steps to implement generative AI in your business: Gather insights, create guidelines, sprint toward first project, invest in education, plan for future of AI
Implementing generative AI in your business can be a game-changer, and Jordan Wilson from Everyday AI shares five simple steps to get started. These steps include gathering insights from a ground-up committee, creating straightforward guidelines with guardrails, sprinting toward your first measurable AI project, investing heavily in education and training, and planning for a future of what happens when AI works. Wilson, who has spoken with over 120 experts in the field, emphasizes the importance of understanding these steps to effectively use AI in growing businesses and careers. He encourages listeners to share the episode for access to extensive show notes, which offer even more insights on each step. Although the steps may require significant investment, the potential benefits of implementing generative AI make it a worthwhile endeavor.
Companies lag in full generative AI implementation despite priority: Only 4% of companies have fully implemented generative AI, and 73% express concerns over insufficient training, emphasizing the need for a more hands-on approach to AI implementation, starting with a committed team.
Despite the growing priority given to generative AI by businesses, a significant number of companies have yet to implement it fully. According to recent studies, only 4% of companies have integrated generative AI throughout their organization, despite 83% claiming it's a top priority. Furthermore, there's a concern among 73% of people regarding insufficient training for AI implementation within their organizations. These statistics highlight the need for a more hands-on approach to AI implementation, rather than just throwing money at the problem. The process should begin with forming a ground-up committee to gather insights and ensure a bottom-up approach to AI implementation. This approach recognizes that AI implementation is not a top-down directive but rather a collaborative effort. By starting with a committed team, companies can effectively navigate the challenges of AI implementation and reap the benefits of this technology.
Implementing generative AI in a business effectively: Gather insights from employees at all levels, have open conversations, form a fast-moving and inclusive committee, and avoid a top-down approach to ensure a successful and sustainable implementation of generative AI.
Implementing generative AI in a business is most effective when done through a bottom-up approach, where insights are gathered from a diverse group of employees at all levels of the company. This approach ensures transparency, safety, and alignment, and allows for the incorporation of more data and adaptability. It's important to have an open and honest conversation with employees about the why of implementing generative AI, addressing concerns and ensuring that it's used to clear mundane tasks for employees rather than automating jobs. A ground up committee should be fast-moving and inclusive, involving members from various organizations to ensure a successful and sustainable implementation. The top-down approach, which is anecdotal, rigid, and often misplaced, should be avoided. Generative AI is a powerful tool that doesn't sleep or need breaks, but it's crucial to involve and listen to employees in its implementation to ensure a smooth transition and maximize its benefits.
Focus on building understanding and buy-in before implementing guardrails for generative AI: Start with open communication and education to build understanding and buy-in for generative AI before implementing guardrails. Resources like the EU AI act, Hiroshima AI process, and White House executive order on AI can provide guidance.
Companies and organizations need to act with a sense of urgency when it comes to implementing generative AI in their workplaces, but they don't have to start from scratch. They can look to other countries, organizations, and resources for guidance. However, it's crucial not to begin with guidelines and guardrails, as this approach may create unnecessary friction and fear among employees. Instead, companies should first focus on building buy-in and understanding of the technology through open communication and education. The EU AI act, Hiroshima AI process, and White House executive order on AI are valuable resources for companies looking to implement generative AI responsibly. Additionally, combining existing guidelines and policies with new insights gained through a ground-up committee can make the process less daunting. Guardrails are essential for ensuring responsible use of generative AI, making it a good business decision. But, starting with them may cause unnecessary fear and resistance among employees. Therefore, focusing on building understanding and buy-in first is crucial for successful implementation.
Setting guardrails for AI use in business: Implement essential safety measures for your company to ensure ethical conduct and alignment with business strategy when using generative AI. Adjust objectives as needed and consider ethical decision-making and data protection.
Implementing guardrails for your business when working with generative AI is a crucial decision. Think of guardrails as essential safety measures for your company, ensuring that your team, no matter the size, stays within the bounds of acceptable practices and ethical conduct. These guidelines must align with your business strategy, and sometimes you may need to adjust your objectives to ensure harmony. Ethical decision-making is also crucial, particularly when handling sensitive data. Remember, large language models have crawled more information about your company than you might realize, so it's essential to consider data protection and privacy in your guardrails. The specifics of these guidelines depend on your industry, laws, and regulations, so it's essential to consult resources like the EU AI Act, Hiroshima AI Process, and the White House executive order for guidance.
Focus on measurable AI projects for quick results and risk reduction: Companies should start with small-scale AI projects, reduce risk, and demonstrate value to stakeholders. Invest in education and training later. Leverage existing models through RAG instead of creating large language models.
Instead of aiming for grand, unrealistic generative AI projects that may not yield immediate results or even be necessary, companies should focus on measurable and achievable AI projects. Uniseko and the National Institute of Standards and Technology recommend implementing guidelines and guardrails for AI use. For most companies, the first step towards AI implementation should be a small-scale project. This approach offers several advantages: it reduces risk, allows for quicker results, and provides an opportunity to demonstrate the value of AI to stakeholders. Additionally, companies should invest in education and training to align with long-term business goals, but this can come after the initial project. Many businesses are making the mistake of trying to create their own large language models, but for 99% of companies, this is unnecessary and economically unfeasible. Instead, companies should leverage retrieval-augmented generation (RAG) and work with existing models that best fit their needs. By focusing on a measurable project, companies can build momentum and showcase the potential of AI across their organization.
Start small with AI projects: Identify a specific area for AI implementation, demonstrate measurable impact, and build momentum for larger-scale initiatives
When implementing AI projects in a company, it's crucial to start small and focus on quantifiable, transferable wins. Don't aim for a large-scale implementation right away, as this approach can lead to misunderstandings and resistance from stakeholders. Instead, identify a specific area where AI can have a measurable impact, save time or money, and tell a compelling story about the results. This not only minimizes the risk associated with AI technology but also makes it easier to replicate and expand across departments or locations. Education and training are essential ongoing processes that should align with long-term business goals. Remember, the key is to start small, demonstrate tangible benefits, and build momentum for larger-scale AI initiatives.
Shift in business mindset required for AI implementation: Invest in education and training to build trust and improve usability of generative AI, demystifying the 'black box' nature of the technology.
Proper implementation of AI, specifically generative AI, requires a significant shift in business mindset and a deep understanding of the technology. This unlearning of old business habits is crucial before implementing any generative AI tool. Education and explainability are key components of this process. Most people lack trust in generative AI due to the "black box" nature of the technology, so it's essential to demystify it and provide explainability. This can be achieved through training and education provided by vendors and outside experts. By investing in this education and training, organizations can save time, increase trust, and improve the usability and outcomes of their AI implementations.
Creating a safe space for AI experimentation: To successfully implement generative AI, foster a culture of learning, clear communication, and ongoing education and training for employees.
Implementing generative AI in a company requires careful planning, education, and training. It's important to create a safe space for employees to experiment and learn, just like a sandbox for children. This doesn't mean that everyone needs to become a tech expert, but rather that clear communication skills are essential for working with AI. Additionally, before deploying AI projects company-wide, it's crucial to explain the implications and train employees on the big picture. Lastly, it's essential to have a plan for the future when AI becomes integrated into the company's operations, including addressing potential job displacement. Overall, the successful implementation of generative AI requires a culture of learning and a commitment to ongoing education and training.
Transforming businesses with AI: More than just automation: Implementing AI in businesses involves careful planning, ethical considerations, and a focus on long-term goals to automate tasks, free up time for meaningful work, and create a happy workforce.
Implementing generative AI in businesses is a significant transformation that requires careful planning and consideration. It's not just about automating tasks, but also about freeing up time for more meaningful work and creating a happy and productive workforce. The process starts with gathering insights from a diverse group of employees, then creating clear guidelines and guardrails. After that, businesses should start small with a measurable AI project, invest in education and training, and plan for the future when AI becomes more integrated. Ethical AI implementation is also crucial, which means treating employees ethically and envisioning a hybrid approach where humans and AI systems work together. The potential of AI to be a game-changer for businesses is enormous, but it requires careful planning and a focus on the long-term goals.
Collaborative approach to implementing generative AI in business: Hire an internal chief AI officer and external consultants for a comprehensive strategy, consider customer impact, and communicate effectively for time-saving and improved customer service.
Implementing generative AI in a business involves a collaborative approach between internal and external resources. Mauricio recommends both having an internal chief AI officer and hiring external consultants to ensure a comprehensive strategy. In step 5, it's crucial to consider the impact of successful AI implementation on customers and communicate effectively. Tangible case studies and return on investment studies exist across various industries. Overall, the goal is to free up time for better human engagement and improved customer service. Sign up for the Everyday AI newsletter for more resources and insights on leveraging generative AI for business growth.