Your Guide to Successful AI Adoption: 5 Tips for Business Decision-Makers

Artificial intelligence (AI) has a significant impact on a business, and a business decision-maker must be prepared for implementation. The decision of whether or not to adopt AI is a crucial one that will have a lasting effect on the company’s future success. In this article, we provide five tips for successful AI adoption as a guide for those who are making decisions about implementing AI in their companies.

After reading this article, you’ll know:

1. What are the most common challenges of digital transformation and AI implementation?
2. Which problems can the AI adoption solve?
3. How does AI Design Sprint look like, and why is it worth participating in it?
4. Why Agile methodology works well for AI projects?
5. Which technical aspects to consider when implementing an AI solution?

Just like cryptocurrencies, artificial intelligence-based tools and technologies have entered the mainstream faster than most experts have predicted. Interestingly, it’s the pandemic that accelerated their adoption, forcing companies to search for a way out of the crises by trying new strategies for business growth. Many had already been slowly preparing for the AI digital transformation before, but the covid outbreak made them implement these changes at a much faster pace.

If you’re reading this blog post, you most likely are considering AI adoption or have already taken the first steps towards it. Thus, we probably don’t have to convince you that it can make the business processes more effective, free the employees from mundane and work-intensive tasks, or reduce the number of errors, not to mention other potential benefits. Whether you’re representing a small startup or a well-established organization, the tips below will help you maximize the benefits of AI implementation. Let’s now focus on how to access them.

Do Your Research and Identify Potential Opportunities for AI Implementation

Like any other technology, artificial intelligence should be implemented consciously – otherwise, it may do more harm than good. Companies often adopt new technologies spontaneously to keep up with the competition. That can be a sabotaging move since it generates additional costs without addressing specific issues. Any innovation should start from problem identification - and in the case of adopting AI, it’s no different. Most commonly, the entrepreneurs use it for solving such issues as:

• skills shortage
• low productivity
• low cost-effectivity
• low user engagement
• insufficient human resources

But that’s just the tip of the iceberg – artificial intelligence technologies, particularly machine learning, can do much more than this.

To make the most out of the AI’s potential, it’s worth organizing an AI Design Sprint – a set of workshop sessions structured with the Design Thinking approach. Since the customer needs are always its core focus, the solutions prototyped in the DT mindset have much more chance to fulfill the customer-oriented business goals (you can read more about Design Thinking & AI in our article).

During such a sprint at nexocode, we empathize, define, ideate, prototype, and test in an iterative manner to ensure the implemented AI tool really does its job instead of becoming another technology to sustain without tangible outcomes. And all this happens in just two days! On the first, we focus on problem identification and ideation. We end the ideation phase with a finished AI Proof of Concept that evaluates the potential of a particular AI strategy and its business value. The second day is dedicated to feasibility, data discovery, and planning, leaving you with a set of prototypes at the end of the session.

If you’d like to know more about the AI Design Sprint, visit our page dedicated to this service or download a free ebook (no e-mail needed!) that explains this process to the smallest detail.

Gain an Understanding of AI Technologies Before Committing Resources

Chatbots, personalized suggestions, self-driving, visual recognition, navigation, natural language processing – all these inventions are fueled by artificial intelligence/machine learning, and they’ve already become an essential part of our everyday life ( here, we list examples of its practical applications). Despite the ongoing debate around the ethics of AI, entrepreneurs don’t approach it with extra caution anymore. This sudden shift to the mainstream has already changed the face of many industries, particularly finance and healthcare. However, AI’s negative publicity is still taking its toll, leaving some to fear losing control over the algorithms.

But, as Janelle Shane claims in her brief yet fascinating TED talk, we should not worry that artificial intelligence will turn against us but rather that it’s going to do precisely what we ask. Even the most sophisticated algorithm fails once it’s given the wrong problem to solve. It’s essential to remember that, in the end, this powerful tool depends on our decisions. And thus, the support of qualified professionals is crucial to the project’s success.

The very first step business leaders should take on the path to AI adoption is to define their expectations from a specific AI system. What kind of predictions, optimizations, automation, or suggestions do you expect the algorithm to make? How will it affect your workflow processes and day-to-day activities? Which additional benefits can a machine learning system provide beyond its core functionality (it might be more cost-effective, for example)? These are some questions that need answers before committing resources to implement a particular technology. However, even with a clear idea about what we want our artificial intelligence solution to achieve in general terms, there’s still much work ahead when it comes to details – creating a feasibility assessment, choosing appropriate AI technology, of the future application, and setting up a roadmap are both essential steps towards successful project completion.

That’s why, during Nexocode’s AI Design Sprints, the AI engineers and data scientists join forces with the client’s team to come up with the most effective solutions. They’re always at your disposal to break down the most complex AI-related issues in a friendly manner. They help the client decide:

• how the data transformation will be handled (automation may help with its cleaning and preparation for data modeling)
• how much data your algorithm will process (quality over quantity is the rule that applies not only to AI-based systems – but for the machine learning algorithms, it makes a difference)
• how frequent the AI/ML model updates will be (the frequency of updates have an impact on its performance)
• which type of ML solution or architecture will be the best for their project (will it be a simple machine learning model or will it use advanced AI technologies like deep learning? will you need to facilitate AI integration with various systems and scaling up in the future)
• how to approach the ethics of AI solutions and data privacy issues (what kind of ethical implications are connected to your future AI technology? how to handle data collection and further usage to ensure safety?)

… and solve many other doubts that arise when adopting AI to a particular project.

Understand the ROI of AI and Risks Associated With Implementing Artificial Intelligence Into Your Business Model

AI can help you identify the business risks through the advanced prognosis based on data analysis. But its implementation can be a business risk itself. It may require increased computing power, mass memory extension, or other IT infrastructure modifications to effectively process big data. The exploration of these aspects is fundamental to the risk assessment. We recommend estimating their short-term and long-term costs to calculate return on investment. How to do it? We explain it in this blog post.

It’s worth noting that ROI calculation is more challenging in the case of AI projects than the regular ones due to the transformational character of this technology. Usually, such solutions are not one-time investments. To make the most out of it, the company may need to invest in upskilling and requalification, not to mention technological resources. When calculating return on investment, it’s essential to include these hidden costs.

Build Relationships With Experts Who Specialize in AI Adoption and Implementation

Reaching out for professional support to adopt AI is the best preventive measure against missed investments. A company experienced in this sector can help you identify potential areas of improvement and business benefits, calculate ROI, and select matching technologies. Even if you hire employees with a background in AI and ML, a fresh perspective is always an added value. The external partner may notice the opportunities and issues that the team members miss since they’re so immersed in the project. Another benefit is having access to the wide professional experience of AI experts and data scientists that each consultant brings.

The best partners are not just a source of knowledge and expertise. They’re a ready-to-hand pool of professionals with a proven track record in the industry who can be mobilized at any time to assist your staff and save you money on recruiting, onboarding, training (as a rule, AI consultants are experts trained in various technologies). This approach saves resources by reducing the amount of administrative overhead that often comes along with employing new employees or getting additional contractors for short tasks within a project team.

Finding qualified AI specialists is difficult due to increased demand on the market, and hiring them – quite costly. A cooperation with an external partner is a convenient alternative. You instantly access priceless expertise, insights gathered throughout various projects, and a specialized set of skills and tools. For your team members, the experience of working with an AI company may be an opportunity to upgrade their skills and prepare themselves for the further stages of AI implementation.

If you’re looking for an agile-oriented partner, reach out to us – we will help you adopt AI in a risk-free and customer-focused manner.

Approach the Project in an Agile and People-Centric Way

Most AI projects are carried out in an agile way, and there’s a reason for that. Most companies do not have much experience with AI, and agile methodology works perfectly in such cases. With waterfall, the team has to go all in, and with agile, its members can take smaller steps, discovering the potential of this complex technology through the prism of a particular project. Working in short sprints makes it much easier to detect potential issues and react to changing priorities.

Agile methodology is perfect for a customer-centric approach and is especially important in AI technologies. It allows for a flexible approach to AI initiatives and enables change of course when the client’s needs or goals change during the project. The customer can be involved in every step of the process, from requirements gathering to product delivery and even after that, when it comes to further improvement and fine-tuning. This way, you’re sure that the delivered solution meets your exact needs.

If you’d like to learn more about the benefits of AI agile project management, we recommend reading our article on agile AI practices. It lays out how the idea becomes a complete product in an agile process and outlines the advantages and disadvantages of this popular methodology.

Summing Up

There is no doubt that AI solutions have great potential in terms of business benefits. However, the complexity of the AI systems and the rapidly evolving character of this technology require a particular approach in both design and development phases. With our support, the whole process can go smooth and risk-free. Thus, regardless of your company’s size and sector, we encourage you to contact us. Let’s talk about your idea and come up with the solutions together!