Is your company ready for AI?

Many businesses are considering integrating AI into their workflows and products but don't know where to start. This guide will help you assess your AI readiness and prepare for next steps.

 

The technology landscape is changing faster than ever, and companies are eager to leverage AI to improve operations. Just like the software boom of the early 2000s, artificial intelligence will revolutionize the modern business.

But considering that up to 80% of new AI projects fail, is AI a safe investment ? It's important to know if your company is ready for AI and where to start. Discovering your organization's AI readiness is the first step to harnessing AI for your business.

 

What is AI readiness?

This is a measure of how ready a business is to use AI effectively. This includes having the right technology, high-quality data, skilled workers, and an organizational mindset for success. Understanding your AI readiness helps identify areas for improvement and gives you ideas for potential AI applications to enhance your operations.

Key Factors Indicating AI Readiness

Strategy towards the future

How clearly do you outline your needs for the next quarter, year, and five years? A clearly defined strategy will inform a useful software development process.

Technology infrastructure

What does your business's current technology look like and is it up to date? Make sure it aligns with best practices and can support AI implementation.

Data Infrastructure

Where is your data stored, organized, and accessed? High-quality, easily accessible data is critical to optimizing AI.

Operating efficiency

How streamlined is your current operation? Analyze workflows to identify areas where AI can streamline processes and increase efficiency.

Organizational culture

Think about your organization's ability to adapt to change. Successful AI implementation requires a culture that embraces innovation and manages change.

C-Suite Support and Organizational Culture for AI Implementation

One of the biggest barriers to AI readiness isn't technology, it's people. AI will change the way work gets done, and many jobs are likely to evolve. Think about how your team handles change and consider ways to help them adapt.

Equally important is ensuring that the C-suite sees the value of AI. They may think of exciting applications that can create images, videos, or promise to write the next great movie. While these technologies may be tangible, business leaders must understand that the true value of AI lies in its ability to automate manual tasks, improve operational efficiency (OpEx), and scale throughput beyond what a human workforce can do.

 

For example, a recent McKinsey study revealed that AI can help software developers work up to 200 percent faster, leading to increased productivity and improved labor ROI. An estimated 30 percent of all current work hours in the United States could be automated as early as 2030—companies that don't take advantage of this trend will be left behind.

Executive buy-in is essential for success. When your leadership understands the benefits of AI to the business, they can champion AI adoption, ensure the necessary resources, and ensure everyone in the company is on board.

A Step-by-Step Guide to Assessing Your Business' AI Capability

If you've determined your organization needs AI—and most companies will in the coming years—you can follow this process to assess your AI readiness.

Step 1: Identify ROI Opportunities

Before deciding to build an AI solution, companies need to understand where AI can help the most. Consider all of your current processes and where your employees spend their time. Consider areas where repetitive tasks require a lot of manual labor, such as data entry, preparing reports, sending frequent emails, creating charts, and manually manipulating data.

Identify tasks that need to scale quickly and easily, such as customer support, marketing, and user onboarding. Also look for areas where AI can improve quality, such as reducing human error in data entry and reporting, ensuring consistent brand and user experiences across platforms, and enhancing quality assurance.

Create a list of opportunities and rank them by potential impact.

Step 2: Analyze the data infrastructure

AI and data go hand in hand. AI needs data to learn and produce useful output. Check the quality and accessibility of your data. Identify the origin of your data, assess data quality, review data policies, and understand how data moves through your company.

Look for ways to improve your data processes and make sure you have enough data to train your AI. If possible, map out your data architecture and identify what is working and what is not.

 

Step 3: Assess the feasibility of AI

Before you begin implementing AI, you must research whether your opportunity is feasible. Because of the relatively novel nature of some AI capabilities, the possibilities are constantly expanding—projects that weren't feasible even a month or two ago may be feasible today. Consider the following factors:

1. Available Technology: Determine whether the technology and tools needed to implement an AI solution exist. Research several industries to see if similar technology or tools are available to build it. You may benefit from speaking with an AI consulting firm to better evaluate your options.
2. Data Availability: Determine whether your data is sufficient, relevant, and high quality to train an AI model to complete the task you intend to automate. Identify any gaps in your data that may hinder AI implementation.

Step 4: Plan Feasibility and Effort vs ROI

After assessing your capabilities and opportunities, plan the effort and feasibility versus ROI to achieve your desired results. List opportunities based on their potential return on investment (ROI). Eliminate any that are currently not feasible or flag them for re-evaluation after a specified period of time. Then, assess the effort required for each feasible opportunity.

Prioritize the feasible option that delivers the most value with the least effort. Focus on tasks that are easier to implement but have a high return first.

Step 5: Identify skill gaps

Humans play an essential role in building, using, and maintaining AI. Identify gaps in your skills and consider options for filling them.

Conduct a Skills Inventory: Examine any current AI-related skills within your company. Identify areas where you lack expertise, such as machine learning, data science, or AI ethics.

Identify the skills needed: List specific skills based on your AI goals. This includes technical skills like programming, machine learning, and industry knowledge.

Training and Development: Consider how you can invest in employee training through online courses, workshops, certifications, and hands-on projects. What resources do you have?

If training isn't enough, you'll need to evaluate your options for additional resources. You can hire new AI engineers or AI developers, work with an agile software development consultancy, or consider staffing up to support the team.