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Top 5 Considerations for Choosing an AI Project

Is your company ready for AI?

In our recent articles we have been discussing how Sway AI makes AI accessible to all. In this article, we will dive further into how enterprises should go about choosing their first AI project, providing you with the top five considerations to bear in mind as you begin your AI journey. Our goal is that you walk away feeling confident that you can lead and champion the implementation of a successful AI project within your organization.

Photo by Ahmed Zayan on Unsplash

Your Organization’s First AI Project

There is no question that artificial intelligence (AI) is reshaping businesses. Implementation of AI is no longer a matter of if but when. Amazon, Netflix, and Apple are examples of companies that have implemented successful artificial intelligence (AI) solutions to enhance the customer experience, automate business processes, and increase their efficiency, productivity, and product or service quality. Examples such as these successful AI implementations have led other and often smaller organizations to launch their own AI projects. Embedding AI and machine learning (ML) is posed to be the single most important trend in business software this decade.

However, it can be difficult to launch an AI program where none exists. Some businesses struggle to find a business problem that can be addressed by AI technology, and others have identified so many opportunities that they don’t know where to start. Still others are stuck in a knowledge gap: They have no experience or in-house expertise in AI and have no idea where to begin.

In this article, we discuss some helpful tips for organizations to consider when choosing the right AI project for your organization.

- Organizational Readiness

One of the first steps while contemplating an AI project is to determine organizational readiness. Organizational readiness for AI is not a given; some team members may not understand what’s meant by AI and its unfamiliar terminology, such as neural networks, machine learning, and deep learning. They might not know the advantages of the technology or its limitations. Some may be suspicious of AI initiatives, believing that AI applications will make their jobs obsolete. In fact, according to an HBR survey, 40.3% of respondents claimed that lack of organization alignment and 24% cite cultural resistance as the leading factors contributing to lack of business adoption of AI. Successful AI initiatives on the other hand are understood and championed by stakeholders and rely on organization-wide participation, communication, and collaboration.

In fact, ensuring your organization is equipped with senior leaders who strongly advocate for data and analytics within their organizations are incredibly valuable, to the success of your AI project. Change management experts even suggest that when readiness in an organization is high, an organization is better able to introduce and support change. When employees and executives within an organization are ready for change, they are more likely to exert greater effort, persevere in the face of impediments, and participate fully in data collection activities. If your organizational readiness is unknown, there are many tools such as that provided by companies such as AGS that can be used to assess organizational readiness before implementing and evaluating a new initiative. An organizational readiness assessment is a valuable way to uncover concerns that need to be addressed in order to make your AI project a success.

- Understanding Business Goals

It is equally important to understand, when you are implementing AI, it may not be a one-size-fits-all, off-the-shelf solution for your organization. Therefore, your AI project should have a specific purpose and associated goal. A good starting point for any company would be “What problem do we need to solve?” When you think about choosing an AI project, one of the first steps is to also identify business processes that can benefit. You need to understand what AI solutions can do — and just as importantly, will that result in your desired goal.

Another important consideration is the availability of good data to support your AI project. “Good data in, good data out,” is a commonly heard saying in the AI world. AI solutions may succeed or fail by both the quantity and quality of the data needed to define the model, train the algorithm, and test it. If you don’t have enough good, relevant data inhouse and can’t get it from any publicly available data sets, then it may be premature to launch an AI project. If you need help with understanding these nuances, make sure you are working with an AI company such as Sway AI who makes this a key factor in your AI project’s planning process. This type of guidance can turn out to be invaluable in the long run. Overall, choose a project that addresses a real business problem with a well-defined scope and results in an attainable goal.

- Real Return on Investment

On the topic of goals, often organizations measure the potential value of an AI solution only in terms of revenue gained or costs reduced, but this approach can be short-sighted. The return on investment (ROI) for an AI-based solution can be judged on three different, complementary levels:

· Business level: profits, revenue, and growth. This is the traditional way to measure the ROI for any solution, not just AI.

· Customer level: products, services, and overall customer experience. This is more difficult to measure in dollars and cents, but there is no doubt that companies benefit by delighting customers with high-quality products and services and with an easy, intuitive, responsive customer experience.

· Employee level: operational workflow and structure. An AI solution that addresses employee pain points and eliminates “grunt work” makes employees happier and more productive. The ROI might be a reduced churn rate.

In evaluating the expected ROI of an AI project, you should examine each of these levels. There may not be a positive impact on every level, and that’s okay, and it is certainly okay for your first project. Setting and understanding ROI expectations prior to a project’s start is wise in order to have realistic goals and expectations for your AI project.

- Size, Complexity, and Risk

Aside from those levels, it’s also important when you are considering the potential results of your AI project that you remember achieving broader results is only possible if you take one step at a time. “Walk before you run,” or in other words, start small with your AI efforts knowing you will ultimately implement larger more impactful projects in due time. A big, complex, high-visibility project, with costly consequences in the case of failure, may not be advantageous for your organization to start with. If this is your first AI project, it might be wise to choose an AI project that lends itself to more of a simple solution. As complexity increases, so does the risk of failure, especially when using new technology. Find a business problem that offers AI opportunities that are reachable, achievable and measurable.

Bottom Line: Keep It Real, Keep It Manageable.

Your first AI project should be less about solving your organization’s most complex problems and more about getting your feet wet: Learn how to think about AI projects, gather good data, define the model, learn the tools and technologies, and so on. But should you have a real business problem to solve, with a real, positive expected gain? Absolutely. A real problem has variability and unknowns that present the team with real hurdles to overcome, and it gives them a better learning experience. But the solution should be small enough in scope and well-defined so that it doesn’t overwhelm a team that is just learning how to apply AI.

One way to reduce the risk in your first AI project is to choose tools that are easy to learn, easy to use, and don’t require extensive technical expertise. For instance, Sway AI’s no-code AI development platform is a seamless tool to start with as it is designed for both AI novices and experts alike. Through its patent-pending drag-and-drop technology, Sway AI enables any user to build AI without needing to write a single line of code. This opens AI to a whole new category of users — the domain experts. Using Sway AI’s platform, domain experts, data scientists and AI experts can collaborate with the necessary stakeholders, build prototypes faster, and dramatically reduce their time-to-deployment, all aiding in the success of your AI project. No-code technology is certainly the future of AI and Sway AI’s technology is the posed to lead the no-code AI market.

- Choosing the Right Price

Lastly, with AI projects ranging anywhere from under 100K to over a million, it is hard for any executive to understand what they should be budgeting for their AI project. A typical AI project is multifaceted, so the price tag includes items such as the developmental tasks of data cleaning, labeling, model training and tuning, and of course the cost of implementation. However, once the project is rolled out, there are the fees associated with the ongoing maintenance otherwise known as MLoPs. Therefore, choosing a company where they offer end-to-end implementation is shrewd, as outside AI services, like consulting, generally cost anywhere from $200 to $350 per hour.

With AI project being innately risky and the cost of implementation and maintenance of such significance, finding the right AI company to deliver on your project is key. Not only is it imperative that the company you choose understands the organizational risk that you are taking but they are involved in all steps of the development, implementation, and maintenance. Sway AI, whose mission is to democratize AI for all enterprises approaches this concern with an unprecedented understanding and solution. Sway AI offers a “starter package” an end-to-end AI project package for those enterprises looking to implement their first AI project. They graciously offer this at half the price of traditional AI projects. Even more impressive is that all steps needed for success of your project are included; from setting realistic goals and understanding the data, to development, execution, and maintenance of the AI project. This full spectrum service is covered for an affordable price. With their low price tag, ensuring that all stakeholders are rallying around your AI project, obtaining a solid ROI and the overall success of the AI project are all but guaranteed.

Interested? Contact us today to learn more about how Sway AI can help you get started on your AI journey.

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Three successful entrepreneurs Amir Atai, Jitender Arora and Hassan Ahmed came together in October 2019 with a few things in common — a dream to solve a real-world problem, a desire to be an industry disruptor and motivation fueled by naysayers. This is where Sway AI was born.

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Catherine Hansen

Catherine Hansen

Catherine believes that creativity is intelligence having fun, and has used that belief to develop innovative marketing solutions for Sway AI.

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