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It’s understandable that people are generally concerned about automation replacing jobs, but gaining buy-in for AI integration is about more than just allaying fears. Rather, the leader’s job is to build confidence that this technology will help them achieve their goals faster and with greater benefit. For companies to successfully navigate this transition, leaders must ensure that people are incorporating their AI to improve and maximize contributions, optimize company growth, and ultimately lead to improved team experience and compensation. need to know.
We have a curated list of projects for next year, and people have already spent months prioritizing them. So I’m very transparent about what I get from AI and machine learning. AI and machine learning will build on our existing roadmap and ultimately deliver a more robust and powerful product suite. This doesn’t happen all at once. A step-by-step approach to integrating AI into workflows and products emphasizes strategic resource allocation and a commitment to continuous learning. It starts at the top, because leaders are on a journey with AI just like everyone else.
Related: Building a human-centered, yet AI-enhanced workforce
Integration: A step-by-step approach
The first goal of integrating AI is to understand the quickest way to start seeing positive financial returns from AI. Our AI project is still a work in progress, but we expect revenue to grow from his $2 million to his $20 million as a result of an initial investment of less than $100,000. But achieving such results requires leaders to become familiar with AI and understand the challenges and complexities they may encounter.
I hire an outsourcing company to build the smallest possible prototype so that I can participate in the ongoing conversation about the most feasible ways to integrate AI. It was similar to when I meet with my CTO every morning to discuss building the flagship product of the business today. We combined his programming knowledge with my knowledge of business goals to make daily improvements and get a minimum viable product to market for testing as quickly as possible. Improving and refining your product begins in earnest by getting real feedback and seeing real-world work performance.
My first goal in testing AI is to power our push messaging system. We send millions of messages every day, and just one person is responsible for creating, scheduling, and optimizing hundreds of different messages. AI allows customization to a previously unimaginable degree, allowing for meaningful performance optimizations that AI can automatically handle. There are other products that should center around machine learning components. By exposing myself, as well as our product and development teams, to the potential of AI, we’re not wasting resources without seeing tangible performance improvements. And for all of this to work, communication must be consistent throughout the process.
Related: 3 practical ways to leverage artificial intelligence
communicate our direction
I am a strong supporter of transparency in all aspects of business. We want our employees to know how the changes we are considering will impact them. But if you don’t clearly explain your goals, misunderstandings can take root. It is important for leaders to express confidence in the direction of AI integration and provide a clear vision of where the investment will take the company.
As companies expand and more people’s ideas compete for limited resources, leaders need to prioritize as accurately as possible. For example, a project that costs $1 and earns $14 should be preferred over a project that earns $3 for every $1 spent. It may seem obvious, but his 3x return on investment is compelling. Prioritizing better yielding projects first means money goes into building more products for less profit.
If you can achieve a positive outcome as quickly as possible with minimal risk, you are more likely to get buy-in from everyone. Start small and build from there. If you can improve your marketing message response rate by 2%, you will have more confidence in applying your prototype to external products. It’s also an opportunity to reinforce our message.
Beware of red flags
As leaders share their ideas about AI integration with a broader audience, they may encounter significant red flags about what you’re missing. Everyone has a different perspective. If you’re a glass-half-full type of person, listening to someone who’s a glass-half-empty type of person can give you a complementary perspective.
When we have an idea that actually moves the numbers, we tend to act quickly. It’s important for people to understand that I’m not rushing AI integration because I’m not happy with our current processes or people.it is because I’m happy not to risk what I already have unless I’m completely sold on the upside. And we want to accelerate the learning process to get those benefits faster.
I still like to talk to as many people as possible, including employees, developers, marketers, product managers, and external investors, about the tone of responses and the big issues. These red flags may be important to consider. Or you need to give people more information. In any case, my response will alleviate their concerns.
Related: 15 years ago, I transformed my company through AI — here’s what I learned
AI and humans: complementary growth
I believe people should embrace AI the same way they embraced computers 20 years ago. Computers opened the door to more new jobs and greater diversity than those they replaced. Leaders must therefore emphasize that AI represents a huge opportunity for growth-oriented employees, balancing increased efficiency and capability with human factors such as creativity, empathy, and ethical judgment. . Think about how you can attract curious employees through workshops, courses, webinars, and industry conferences. With transparent communication and a commitment to continuous learning, people will see AI as a complement to human efforts.
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