Much has been written about the fact that artificial intelligence technology has a great potential to create competitive advantage and value to businesses. However, starting with an AI pilot project and making it work for your whole company aligned with strategy is a challenging task.

Therefore, before diving in several attempts for implementing AI solutions, companies should consider a step-by-step approach with the purpose of providing not only short-term but also long-term benefits for relevant stakeholders. Let us share our supportive list of advice about how to proceed and succeed with an AI pilot project.

How to start with your first artificial intelligence project?

Identify tasks to automate 

When your business is up to engage in an AI pilot project the very first step is to consider what artificial intelligence technology can and cannot do. It means that finding out the areas where value is created in your business and what is hard to be copied will be the key to incorporate AI into strategy and therefore to create business success. Considering business implications of artificial intelligence, the best practise is striving to automate repetitive activities rather than entire jobs with the purpose of replacing or enabling faster task accomplishment through partial automation.

Focus on business context

When you are done with identifying your priority functions to automize, you should put AI technology into your unique business context and customize the value added to the requirements of your stakeholders. This is about understanding of AI technology in terms of business strategy. The task requires an AI leader in the company, who is responsible for building a centralized AI organization and then supports the various business units in terms of AI technology. At this point, business needs rather a talent than technology for integration with the purpose of harnessing AI solutions.

Analyzing the prioritized portfolio of initiatives

After identifying the areas of interest and the method of understanding the technology in your business’s context, the next step is to prepare a portfolio about the areas of highest potential value. Prioritizing and mapping the prioritized portfolio of initiatives will guide your business to gain a holistic view on the places of AI functions and to focus on the certain pilot project delivering the most value for the company.

When AI pilot project is chosen how to proceed successfully?

• Stating desired timeline, outcome and budget
  For every successful project you will need to possess a clearly defined set of goals, timeline outcome and budget. In case of objectives, it is essential to prepare them as to be measurable, which enables business value creation.
• Set up the team
  As it was pointed out before, the role of a well-chosen AI leader could be a key to the success of the project. This person is the leader of the centralized AI team and facilitates the entire unit to work cross-functionally influencing the rest of the organization and thus matrixing in AI talent to the different divisions to drive cross-functional projects.
• Conduct feasibility study
  Besides concentrating on serving the desired outcome and providing value for business it is equally important to keep in mind the technical diligence of the project. Before diving in a project that is impossible to accomplish using today’s technology you should conduct a feasibility study and organize a technical team for carrying out experiments on technology opportunities and data on hand.
• Acquire and organize data and efforts
  Task automation - deploying artificial intelligence technology - can only succeed, when it is built on well-structured database. That is why data engineering is a crucial point of the project; the process of acquiring, organizing, identifying, and measuring useful and valid data, which will serve as the ultimate resource of implementing AI applications in accordance with priorities.
• Developing AI strategy
  As business success depends on companies’ abilities of utilizing AI solutions, we have to emphasize the point of discussing ways to integrate effectively the results of an AI project into the everyday workflow of an organization. This means the true value of an AI model and serves not only the short-term but also long-term interests of businesses. The essence of incorporation lies in the ability of the company to go through the challenges of adapting.  This is the process of aligning AI models with business strategy and also the process of architecting the whole company around AI given capabilities thus building a solid AI strategy.

+1. Organize communication and training throughout the whole process
Since in case of integration - besides technology - the biggest challenges are people and processes, we have to pay special attention training not only our organization from technology and processes’ point of view but also our people. When AI transforms several jobs, it is meaningful to hire AI experts, who will deliver in-person content and motivate your people towards change. Constant reskilling of the workforce throughout the whole process starts from the top, which facilitates the proper flow of information addressing all levels of the corporation and turning strategic perspectives into clear AI ambition.
Along with training, it has a high importance to circulate an effective communication throughout the company in order to back up the change caused by adapting AI. Following a “people first, technology second” approach will promote trust in AI among your key stakeholders. The threat of automation could be eased down by creating transparency through explaining results and benefits of the new technology and providing persistent information about the ongoing changes.

How to ensure the viability of the project?

Start small

A company-wide AI project is able to succeed only in case a “trial” took place first. That is why in case of starting a pilot project, your best chance is to choose initially a program influencing only one or two levels of the company. Although small projects have a smaller impact on productivity, risk of success is less, results could be visible and could deliver a first-hand knowledge about handling an AI project.

Strive for quick result

Considering one of the key stakeholders, the most persuasive reason for investors to engage in AI technology is short-term result. In case you invest in more and smaller projects first using for instance proven technologies, your company will have a higher chance for success and AI projects are more likely to grow based on the trust built. This might be a crucial factor for investing heavily in AI solutions and thus becoming one of the front runners.

Create value for stakeholders

Investing in an AI project requires a huge amount of resources both because of the technology and also the effort to gather the data required to build up a feasible AI technology. That is why, when you are up to work with AI, you have to consider the added value that it delivers first. Organizing vast data alone is not sufficient to operate successfully as an AI centralized company. Value creation through AI is rather happening when you are working with properly set up automation and prediction systems, enabling your company to reduce costs, increase revenue, face new opportunities and new lines of business.

Trust and expertise

In order to become a front runner of AI technologies, it is important to set up AI expertise as soon as possible. Also, in case of possessing an internal team managing AI, projects require continuous support for improvement. On the other hand, if you succeed in building an in-house team for AI in the long run, projects kept within the company will serve as a competitive advantage. The golden mean might be to both operate an AI unit in your company and team up with a credible partner who has the ability to bring in expertise and new waves of AI, too.