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    What does it mean to be AI-Ready?

    Published on 06-Mar-2020 12:00:00


    Artificial Intelligence (AI) and Machine Learning (ML) have burst into the spotlight in recent years getting attention from businesses and all levels of society. Awareness of AI has drastically increased as people become more familiar with how the tech giants are using data to enhance their products and create better solutions. The market is opening up to more AI-infused products, and the public are regularly interacting with AI as it slips into their day-to-day lives through smartphones and virtual assistants.

    Many companies who are taking the plunge with AI initiatives are not coming out on top, and this is usually because they were not AI Ready when they thought they were. So what does it mean for a business to be AI Ready?

    Leveraging ready made AI

    Is there a short cut? Absolutely. Companies wanting to make the most of AI immediately don’t have to go through an AI transformation process or compete with the budgets or talent of the tech giants or larger companies. As prices drop, they can begin by investing in AI-infused products like sales or CRM systems, cutting the need to assemble a data science team before interacting with AI. Businesses can engage in quick-win AI projects like reinforcing their customer service with chatbots, or by investing in AI-powered systems like cybersecurity software.

    That said, it is still a good idea to get your team up to speed with good data practices, you never know your journey will take you in the future, but the future will rely strongly on data. Using ready made solutions may be the best way to start, but eventually, you’ll want to build your own solutions, so there are several steps to take to set your business up for success before embarking on your own AI journey.

    Becoming data-driven

    As we have discussed, it can be easy and attainable for companies to start using AI-products, but getting ready to build your own AI may be a different story. “Doing AI” isn’t really something that can happen overnight. It’s a long process, and it starts with your data and a wider understanding of the AI landscape.

    Let’s talk about data culture. For any company to succeed with their data initiatives, they must foster a healthy data culture. Your team needs to understand how data can drive better decisions, and they must learn to trust the data they have access to. At that, everyone in your company should have access to some form of data! Data democratisation ensures that everyone trusts the data and builds a better foundation for its use.

    Great things can start to happen when everyone is tuned in to the benefits of listening to data. So imagine what could happen when you get everybody on the same page with expectations of AI, too. In order to prepare your organisation for data and AI initiatives, you need to get your staff the right training, workshops, and courses to familiarise them with data practices like proof of concept to ensure projects have value, and how to follow them through to the end.

    Training tailored specifically for executives and senior management can be crucial, as this can help to keep expectations real, and help projects to run smoothly.

    Getting to the data science

    While you can upskill your team, you probably can’t turn them all into data scientists, so this brings about the question, who is going to handle the AI? For this, your business has two options. You can begin to build a data-science team, recruiting new talent and slowly getting the AI ball rolling, or you can contract specialists to execute certain projects for you.

    Option number one, building your own team, can take time and effort, but it pays off in the long run. It can be hard to recruit for data science positions as the demand currently outstrips the supply. But here are some tips to avoid competition when recruiting data science talent.

    For some cases with option two, you may already have begun putting together a generalist data science team, but you need a specialist to guide, or you don’t have a team and you need a consultant to help you meet your requirements. The benefit of working with a consultant is that they can bring years of experience to your very first project. You can pick someone who specialises in what you want to get done, and get started right away. Not only that, but they can tap into a shared pool of knowledge from across their consultancy to apply to your individual problems.

    But how do you find an excellent consultant to work with?

    Addressing your AI-Ready needs

    There are hundreds of consultancies and consultants offering their skills, and sifting through your options can be draining. How do you know where to look and what to search for? Nightingale HQ have created an answer to this problem. Offering a complete AI platform, companies looking to complete AI projects can lean on Nightingale HQ. Using the consultancy search function, companies can single out consultants that work in the desired verticals, with the desired tech stacks, among other requirements. It takes the guesswork out of finding your AI expert.

    In summary, getting down to data science and kicking off your AI journey all starts with getting your business AI Ready. To schedule training for your business, whether it’s aimed at senior management, technical practitioners or a particular department, get in touch.

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    Topics: AI strategy, Data Science, AI adoption, Data culture, AI-Readiness

    Steph Locke

    Written by Steph Locke

    Steph Locke, CEO of Nightingale HQ, is an accomplished data scientist who has helped thousands of businesses during her time working in industry, as a consultant, and as an international keynoter and author.