The path to AI maturity and business transformation
Get critical business strategies for achieving organizational AI maturity and leveraging AI capabilities to drive business transformation.
Feb 8, 2024 • 4 Minute Read
Our AI skills report found that 20% of organizations have already deployed AI, and 55% plan to soon. But AI adoption is only the beginning.
To get value out of AI investments, organizations will need to move towards AI maturity. That’s easier said than done, especially when we’re still uncovering AI’s full potential.
In this post, we explain why organizations need to mature in AI to meet business objectives and provide guidance on an AI maturity model.
Want to learn more about the future of AI and the tech landscape in general? Download the 2024 Tech Forecast.
Table of contents
Why organizations need AI evolution
94% of executives and 92% of IT professionals believe organizations who do not invest in AI in the near future will fall behind the competition. But gaining a lasting competitive advantage with AI relies on more than the technology itself. Organizations need to evolve in AI.
AI investments are on the rise—but AI upskilling isn’t
87% of organizations plan to increase AI spending in the next 12 months. On average, they plan to allocate an additional 17% to AI. But less than half of organizations have training and instruction for AI.
If your organization invests in AI tools without the training needed to use them, you’ll fall short of your goals for AI adoption—no matter how much money you’ve spent.
AI skills are key to creating a culture of innovation
AI will advance other technologies and accelerate a culture of innovation.
“I see the next big skills movement being what I call ‘AI plus.’ AI plus cloud, AI plus security, AI plus data science. All of these existing foundational tech skills can be enhanced and streamlined through effective applications of AI,” says Pluralsight’s CEO Aaron Skonnard.
Your organization needs AI and data skills to understand where AI can impact your business goals and launch you ahead of competitors.
Creating an AI maturity model to meet business goals
Our 2023 State of Cloud report found that organizations need a clearly defined cloud strategy to deliver customer value with cloud computing. In the same way cloud success relies on organizational strategy, AI does, too.
Two of our Pluralsight experts, Faye Ellis, Principal Training Architect, and Drew Firment, Chief Cloud Strategist, chart a course towards AI maturity by drawing on their similar experience with cloud technology and maturity.
1. Define clear business goals
Understand what you want to achieve with AI technology. Maybe you want to streamline repetitive tasks, improve the customer experience with chatbots, or detect security threats faster. Whatever it is, go into AI adoption with a goal.
2. Establish clear metrics for success
Determine how you’ll measure the success of AI implementation. These metrics should tie back to your goals. For example, if your primary goal is to enhance the customer experience, you might measure user engagement rate, agent handoff rate, and overall customer satisfaction scores.
3. Prepare your data
Consider the data you need and any preparation required for AI models to use it. For example, it may need to be cleaned, transformed, or stored on a different platform.
4. Consider different AI models and infrastructure constraints
The right AI model for your organization will depend on your goals and use cases. Consider the pros and cons of pre-trained and custom models, how you’ll validate them for accuracy, and how your current infrastructure may impact your decision.
5. Create AI governance and oversight
Create policies and security measures to ensure data privacy, security, and ethical AI use. Research laws and regulations you may need to comply with, like President Biden’s Executive Order.
6. Invest in upskilling employees
Determine the skills teams will need to understand and work with your chosen AI models and technologies. Provide learning opportunities and hands-on experience for teams to build their AI skills. Encourage experimentation and create a continuous learning culture.
7. Improve AI for business as you go
Start using AI on small projects. As you go, track success, gather feedback, and make improvements. After a while, you’ll be able to refine best practices and streamline operations.
Want more details? Check out Faye’s article on developing an effective AI strategy.
AI transformation won’t happen overnight
Organizations are still struggling to mature in the cloud and drive value with cloud computing. Don’t expect AI development to happen overnight, especially when AI providers are still developing.
“We need the AI vendors to reach a steadier state with their tech before businesses have an opportunity to even approach AI maturity,” says Tim Warner, Principal Author for IT Ops at Pluralsight.
Prepare for turbulence on your journey to AI maturity. “We should expect a lot of false starts, dead ends, and rabbit holes with this,” says Simon Allardice, Creative Director and Principal Author at Pluralsight.
“And that's okay; everyone's going through it. Part of the early stages of maturity is getting past the, ‘If we have a hammer, everything looks like a nail' syndrome. We're seeing that a lot with GenAI—a mad rush for organizations to be seen using it, even if it doesn't fit the project.”
Make AI maturity part of your organizational strategy
To use AI to transform your business, you need to develop an AI strategy that maps to business goals and includes skill development. Pluralsight’s AI solution can help you and your teams get started.
