正在学习
AI in the Enterprise: Proceed with Care (1)
AI in the Enterprise: Proceed with Care (1)
Leveraging AI in an organization demands careful, proactive consideration of many additional factors. It’s not just about more people to coordinate and align on using AI productively; it’s also critical to anticipate and understand the broader and downstream impacts of your AI adoption. This means you’ll really need to explore as a team how AI can support strategic objectives while managing the new risks and responsibilities it introduces. This involves asking tough questions and considering long-term consequences—and this is hard but critical work. The sooner your team learns to work responsibly with AI, the better prepared you’ll be to navigate the inevitable changes it will bring to your industry and market space.
I want to emphasize that the Team Learning Journey shared in this chapter works for a team’s journey of learning how to think with AI. When it comes to developing AI products and services that will impact the people your organization serves—whether internal tools or customer-facing solutions—and taking these to production, you need a completely different, more rigorous process. That process requires extensive testing, evaluation, and compliance with security measures, data handling practices, governance policies, and ethics protocols. As you transition from exploratory learning to developing actual products and services, it’s crucial to closely align with your organization’s established processes, guidelines, and governance frameworks to ensure responsible and ethical AI development practices.
| Speed to Learn over Speed to Launch |
|---|
| There can be great pressure to get AI solutions out the door. But with the space moving so quickly, data infrastructure that still needs work to truly leverage new AI capabilities, and best practices still forming, only the most sophisticated teams have the potential to rush into production without problems, and even these teams have made some very visible and embarrassing missteps. This is a great time to aim to be right to market over first to market. In the Wild West that AI is in these early stages, moving carefully will help you maintain trust with your customers and other stakeholders. Unless you’re an AI company—where competitive pressures demand rapid product launches—I advise my clients to focus on accelerating their learning and increasing the efficiency of that learning process over rushing to bring AI products to market. Prioritizing learning and the deliberate strengthening of AI muscle can lay a strong foundation on which to steadily advance your AI capabilities. And helping your teams to work through the approach outlined in this chapter is a fantastic way to accelerate this learning while simultaneously extracting real business benefit from AI. |
Growing Your Team’s AIQ: Start Small, Think Big
The unprecedented pace of AI advancement has created a unique moment in time: from entry-level employees to seasoned executives, nearly everyone is simultaneously embarking on this learning journey, regardless of their previous experience with artificial intelligence. This reality presents an extraordinary opportunity: we’re all early explorers—and every team has the potential to pioneer something new.
By adopting the learning-centric approach outlined in this book, teams can begin building their AI capabilities no matter how much experience they have. These initial steps are far from trivial. Each interaction, each lesson learned, and each small success builds your team’s collective AIQ. This incremental progress can not only enhance immediate team performance but lay a foundation for more ambitious AI initiatives in the future. Every team’s AI journey begins with a single step. Those who start now—even with modest initiatives—aren’t just learning about today’s AI; they’re building the collective capability to harness whatever remarkable developments tomorrow brings.
Notes
1 “Don’t Let Gen AI Limit Your Team’s Creativity,” Harvard Business Review, March 2024, https://hbr.org/2024/03/dont-let-gen-ai-limit-your-teams-creativity.
Afterword
Every so often, a technology emerges that fundamentally alters the course of human civilization. Now we face a profound moment: a technology so powerful it blurs the boundaries between human and machine and catapults us into a future where the definition of “possible” is rapidly redrawn.
Like every transformative technology in human history—from the printing press that democratized knowledge, to the steam engine that powered industrialization, to electricity that reshaped daily life, to the internet that connected minds across the globe—AI morphs to the intentions of the hand that wields it.
Every powerful tool carries dual potential: a surgeon’s blade can heal or harm, an author’s pen can illuminate or obscure truth. Even the internet, while creating the world’s greatest library, has also become its most prolific source of misinformation.
Already we see AI following this pattern: accelerating medical breakthroughs while powering sophisticated fraud, helping teachers personalize learning at scale while also scaling the generation of harmful misinformation, expanding human creative potential while threatening the livelihoods of people in long-established careers.
This duality is integral to the story of human innovation. When we release powerful technologies into the world, they become mirrors reflecting the full spectrum of human nature—our highest aspirations and our darkest impulses, our drive to create and our capacity to destroy, even our most mundane struggles and needs. What’s different about AI is both its unprecedented power and the staggering speed of its evolution. We’re witnessing what may be the fastest technology innovation and adoption cycle in human history, with capabilities advancing not over decades but months.
While we can’t control every aspect of AI’s development, we can choose how we engage with it. We can make a choice to apply it toward ends that matter—to amplify the positive impact we hope to have.
This is why I’m focused on helping people understand and harness AI’s potential to make positive change. Whether you’re working to solve global challenges or strengthen your local community, supporting your family or building a business, teaching students or leading a team—your ability to thoughtfully leverage AI can amplify your unique contribution to the world.
练习题
Which of the following is NOT a critical factor in AI adoption within an organization?
What are the key components of the process for developing AI products and services?
It is advisable to prioritize speed to launch over speed to learn when adopting AI in an organization.
The text suggests that aiming to be ___ to market is better than aiming to be first to market in the early stages of AI adoption.
Explain the concept of 'Growing team's AIQ: start small, think big'.
What is the dual potential of powerful tools like AI, according to the text?
Which of the following are benefits of forming smaller 'learning circles' for AI exploration?
Storytelling is an ineffective tool for communicating the organization's AI journey and its challenges.
The text suggests that ___ checks should be implemented to assess the team's AI learning progress.
What is the importance of discussing AI ethics in team meetings?
When developing AI products and services, which of the following is a critical step to ensure responsible and ethical AI development practices?
Which of the following are key considerations when leveraging AI in an organization?
It is advisable to rush AI products to market to gain a competitive edge, even if the data infrastructure is not fully developed.
To ensure responsible AI development, it is crucial to align with the organization’s established processes, guidelines, and governance frameworks, including ___ protocols.
Explain how a team can balance the need for speed in learning AI with the need for careful consideration of broader impacts and risks.
登录后解锁笔记、知识点解析、AI 问答
立即登录