How to Develop Effective AI Strategy for Your Business?
Updated on Dec 1st, 2022
Nowadays, most companies agree that Artificial Intelligence has astonishing transformative powers and is necessary for smooth business operations and effective customer management. From healthcare to telecom, businesses in almost every industry are, at the very least, considering adopting AI.
And why wouldn’t they?
With so much data being generated, it would be counterproductive not to use that data to draw actionable insights that can help build more brand recognition and increase revenues.
However, although AI adoption can change how any organization works, it requires meticulous planning based on set goals and success evaluation criteria. Most companies these days have set data and AI strategies to help them build more robust and secure data repositories and use them effectively to build evidence-based business plans and strategies.
Successful AI adoption hinges on well-thought-out AI strategies that consider all the risks, ROI, and roadblocks. At the end of the day, AI, while transformative, can be too turbulent for a business, which can end up doing more harm than good. That is why a sound AI strategy should be the first step in any organization’s journey toward extreme automation.
If you’re still wondering why you need an AI strategy, then this blog post is for you. In it, we will learn what AI strategies are, how you can build one, and what are its prime benefits for businesses.
- AI strategy helps companies define long term plans and goals for their AI adoption.
- AI strategies need to be well thought out in advance since AI adoption is an expensive endeavor that requires a lot of financial and time investment.
- Having clear AI goals and use-cases will help you in being cost-effective and efficient.
- Before launching long-term plans, it is always prudent to try to finish a couple of smaller, quick AI goals to boost morale.
- AI strategy hinges on a company’s data strategy. An AI can’t function without relevant data and so how a company collects data is crucial while building an AI strategy.
But before we get to that, there are two things we need to learn first:
Table of Contents
What is a Data Strategy?
A data strategy is a company’s long-term plan about how to use their data, what security measures to use, what technologies to employ, what will be the governance and access policies, who will be allowed access to the data, what will be the rights of the data creators (customers), etc. All these things combined create a thorough data strategy that helps companies manage their ever-growing data repositories smoothly without any major issues. Most companies that depend heavily on customer data understand the value behind managing and using it properly. That is why they seek data science consultation services from industry-leading data science experts like Matellio.
What is an AI Strategy?
An AI strategy depends on a company’s data strategy. Simply put, an AI strategy defines the purpose behind AI adoption, the technologies to be used, what will be the evaluation criteria to gauge the success of the AI strategy, etc. These elements come together to guide AI adoption progress and help companies course correct if the specified goals are not being met. AI strategy is a road map, much like a data strategy, and not only describes how an AI will be used but also what its ROI will be, whether the company will need to scale up its workforce, what particular type of skills it will require, etc.
It may sound vague, and many companies struggle to build proper AI strategies because they don’t know where to start. That is why hiring an AI consulting firm is the best course of action for people who are just getting started with their AI adoption.
A company’s AI strategy depends on its data strategy. An AI needs data to be of any use. Without it, it can’t learn; if it can’t learn, it’s a useless block of code. So while building an AI strategy, companies often have to go back and revise their data strategies to ensure that their infrastructure is modern enough to work with cutting-edge AI technologies.
How Do You Build an AI Strategy?
While hiring an AI consulting company to build your AI strategy for you is more prudent, if you want to build one yourself, then you can use the following steps. But keep in mind that every company faces different challenges and has different goals. So, there is no one-size-fits-all template when it comes to building AI strategies. At the end of the day, your unique needs and results will play a key role in your AI strategy.
Review your business strategy
Before getting started with your AI strategy, review your business strategy. The end goal of building an AI strategy is to adopt AI in a fashion that can help you reach your goals. So those goals must reflect the investment that you are about to make. These goals should be adequately scaled up and should talk about the company’s long-term goals and how what role AI will play in them. While reviewing your business strategy, ask yourself the following questions:
- Have your goals changed since the last time you revised your business strategy?
- Are your goals current and aligned with the rest of the industry? For instance, using social media presence as a revenue stream is a goal that has only recently come into the picture. So not having it as a part of your business strategy will mean that you can’t use AI to perform complex and extremely beneficial operations like customer sentiment analysis, trend detection, customer behavior analysis, etc.
- Is your business strategy still right for your company and works well with your new, more ambitious goals?
Define your AI use-cases
In this step, you need to clearly define what purposes you’re thinking of AI adoption for. What goals are you trying to achieve with the help of AI? You can’t make an investment this big without having an end goal and a list of use cases in mind. Furthermore, it would be better to restrict yourself to 3-4 AI use cases in the initial stages. You don’t want to bite off more than you can chew in the initial stages. As your AI implementation matures, you can start adding more use cases. Some examples of AI use cases are:
- We want to build a more streamlined customer support process.
- We want to automate the bookkeeping process.
- We want to cut down on production costs and time by automating the manufacturing processes in our factories.
Also Read –How is AI Transforming Software Engineering?
Build a list of short-term AI goals
AI implementation is a long process that can take months, if not years, to show actual, significant progress. Streamlining customer support or automating the entire back office paperwork process can take a lot of time to complete is why it is smart to create a list of smaller goals that you can achieve quickly. Not only will it give you some experience before you tackle bigger challenges, but it will also lay down the groundwork for future endeavors. Furthermore, a couple of quick wins will boost the morale of your team and investors and get them more excited about future possibilities.
Revisit your data strategy
AI is nothing without a constant supply of relevant data. That is why a company’s AI strategy depends on its data strategy. So while building your AI strategy, you should also review your data strategy. While doing so, you should ask the following questions:
- Do we have enough relevant data to achieve our AI goals?
- If we don’t have the required amount or type of data to build an AI that can achieve the goals set forward by our strategy, then how do we do it?
- How will we get more data? Will we have to set up new avenues and capture data ourselves, or do we use third-party data?
- What changes can we make to acquire an adequate volume of relevant data in the future?
Think of possible ethical and legal issues
The fear of a super-intelligent machine controlling and lording over humanity is something that has only grown closer to becoming a reality in the minds of many people in recent years. As we become more connected, thanks to the incredible technological leaps that we have made in the past couple of decades, we have also gotten a lot more dependent on machines. It is impossible to imagine life in this day and age without machines. And when we throw an intelligent piece of software capable of learning and then making far more logically sound decisions, we have a population in a frenzy. That is why, before implementing AI, you should consider all the ethical implications of using AI and customer data for your strategic goals. While coming up with this list, you should ask yourself the following questions:
- Is it ethical to use AI to achieve our goals?
- Do the strategic goals we have formed threaten the privacy of the customers?
- Do we need user consent to use their data as we’re planning? If yes, then what would be those consents?
- How can we ensure that our AI will not have discriminatory tendencies towards a particular race, gender, or ethnicity?
Evaluate your technological prowess
All the planning in the world would do you no good if you didn’t execute it properly. And to achieve your AI goals, you need a slew of modern technologies and AI business tools. The problem is that companies often don’t evaluate their existing infrastructure and dive nose-first into AI development. But it’s not possible to get too far without the proper tools. And once they realize that they are severely ill-equipped, they have to go back and rework their AI strategy. They will either have to change their goals or bring them down to the level that can be achieved with the tools that they have. Or they will have to allot more budget and invest in getting new infrastructure. This entire mess can be avoided by simply taking the time earlier in the strategy phase and conducting a thorough evaluation of your resources. Ask yourself:
- Do we have the right resources in place to achieve our AI goals?
- What AI technologies do we need?
- What will be the investment and ROI?
If you’re not sure how to go about evaluating whether your company’s infrastructure is AI–ready, then you can partner up with a firm like Matellio that offers top-notch technology consulting services to businesses from all verticals and of different sizes.
Evaluate your workforce
Tools and technologies are only as good as the people using them. That is why at the heart of making intelligent machines are humans. So, evaluate your workforce and compare it to the technologies you plan on using. For instance, if you will be working with machine learning, you will need people experienced and trained properly in ML. Again, it’s best to know all the things you need before going in. And if you don’t want to hire full-time AI experts, you can partner up with staff augmentation firms like Matellio and scale your workforce up and down as the need emerges.
Build an implementation strategy
Now that you have planned all the other aspects of your AI deployment, it’s time to think about how you will implement your AI strategy and what will be the method of delivery/deployment. Ask yourself the following questions:
- How will we deliver or deploy our AI project?
- Once delivered/deployed, what’s next? What are our future goals, or what use case do we want to target next?
- How will we gauge the success of the project? Which metrics will we look at?
- How will we course correct if the goals are not being met?
- What will be the project deadline?
Matellio Can Help You Build Sound AI Strategies.
As a custom AI development company and technology consultation firm, Matellio houses a team of highly skilled AI consultants, designers, architects, and developers with years of experience delivering top-notch results. When it comes to AI implementation, we know that there are no shortcuts. That is why we take every tiny thing, every small aspect of your business strategy and goals, while building AI strategies. As an AI consulting firm with a track record in delivering sound AI solutions for businesses from a variety of sectors, we understand the value of planning and know how to implement strategies in a fashion that not only smashes short-term goals but builds upon them to make long-term goals not just achievable but inevitable.
If you want to learn more about our AI development services, then please get in touch with our experts for a free consultation call.
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