Get the latest news in your inbox
AI can revolutionise your company's operations, enhance decision-making, and provide insights that were previously unimaginable. But just like the success of any car journey requires a few key elements for success, to unlock the true potential of AI, you need to prepare your organization effectively.
So, let's dive into the three critical areas you should focus on: being fueled by data, setting the rules of the road, and mapping a good course.
Step 1 - Fueled by Data: Filling the Tank
We’ve been hearing for years that ‘data is the new oil’. And nowhere is that analogy more accurate than AI and ML, where it truly is the fuel. But just like anything, the quality of that fuel will determine the performance of the engine.
AI is a data-hungry beast, and the quality of the data it feeds on is paramount. Garbage in, garbage out, as they say. To get your company AI-ready, it's time to sort through your data, clean it up, and make it AI-friendly.
Start by taking inventory of your data. What do you have? Where is it stored? Is it organized? More importantly, is it accurate and clean? AI thrives on clear, complete, and correct data. Just as a car can't run on dirty or contaminated fuel, AI can't function properly if your data is riddled with errors, incomplete records, or inconsistencies.
Create a data strategy that includes data collection, cleansing, standardization, and validation processes. Invest in data quality tools and ensure that your team is trained to maintain data integrity. Remember, AI will amplify the issues in your data, so it's crucial to sort them out now.
Just like a learner driver, AI doesn't become proficient overnight. The more kilometers it drives the better it gets, and for AI those miles are historical data. The more data you can provide, the better AI can understand your business. Don't worry if you're just starting; you can begin collecting and storing data now for future AI initiatives. But don’t wait until your competitors are deploying their models before you even start to collect and prepare the data needed for your own.
Step 2 - Setting the Rules of the Road: Managed by governance
In order to confidently get behind the wheel you need to be assured that you and the other drivers around you will follow a set of agreed rules. By providing such guidance you are more likely to get where you want and less likely to face a horrible accident on the way.
AI is the same, to manage AI effectively this means establishing governance structures to oversee both the data and AI processes.
These are the core rules that make everything else possible. Road conditions, road markings, lanes, and signage. Data governance ensures that your data is collected and managed effectively, as well as used responsibly and ethically. It involves creating policies and procedures for data collection, storage, access, and sharing. Implement data access controls to protect sensitive information and comply with data privacy regulations and consumer expectations.
These are the etiquette and usage rules. Think give way rules, traffic lights, speed limits, and safety barriers. AI governance focuses on the responsible development and deployment of AI systems. It includes defining the rules and ethical guidelines for AI usage within your organization. Ensure that there's transparency in AI decision-making processes and mechanisms for accountability.
This is how you can make sure that everyone on the road is following the same understanding of how it’s meant to work and to ensure that that doesn’t change day-to-day. Document your AI projects rigorously. This documentation should include data sources, model development, testing, and deployment procedures. Well-documented AI projects are easier to manage, maintain, and scale. Establish operational processes for monitoring AI performance and addressing issues as they arise.
Step 3 - Charting the Right Course: Aimed with Accuracy
Finally, to achieve the desired end goal, you need have a plan of where you’re going and why. AI is most effective when it's aimed at solving specific business problems. To prepare your company for AI, you need to identify the right use cases.
Think of your business units as passengers in your AI-driven car. Engage with them to understand their pain points and challenges. Who get scar sick, who has a small bladder, who wants what music, and what’s the fastest way to get somewhere. AI is a tool to solve real-world problems, and your colleagues on the frontlines often know best where it can make a difference. Collaborate closely with them to identify use cases that align with your company's goals, or you’ll get off track.
Not all use cases are created equal. Prioritize them based on potential impact and feasibility. Start small with pilot projects to test AI's effectiveness in real-world scenarios. This allows you to fine-tune your AI models and gain the confidence of your team.