3 Steps to Build an AI Foundation

An artificial intelligence (AI) strategy is only as strong as the foundation on which it is built. Having a solid AI foundation leads to quicker implementation of AI and greater chances of success for a long-term AI strategy. Without a strong foundation to hold up an AI strategy, organizations can’t take advantage of the increased speed and accuracy of strategic decision-making processes AI can offer.

What’s ahead: In this article, we’ll cover:

• What is artificial Intelligence
• 3 steps to build an AI foundation
• Quality data
• AI talent
• Organization-wide buy-in

What is Artificial Intelligence (AI)

Artificial intelligence refers to systems or machines that mimic human intelligence to perform tasks and can improve themselves over time. AI is powered by advanced algorithms and learns by combing through large sets of data and picking up on patterns or features.

Uses for AI include:

• Voice recognition – AI pulls in answers to your questions or performs the tasks you ask
• Chatbots – AI can be triggered by certain words to output a certain response, learn and adapt to certain responses, and more
• Online shopping – AI is used to learn about your purchasing habits to predict what you’ll shop for next
• Streaming – AI learns your streaming preferences to make suggestions
• Finance – AI takes the emotion out of investing to make analytical decisions in a matter of minutes
• Healthcare technology – AI can learn about patients and adapt over time to improve care
• Manufacturing – AI automates processes for more accuracy, efficiency, and safety

Between 34% and 44% of global companies surveyed for a Harvard Business Review Study use AI for the resolution of employee tech support issues, the automation of internal systems, and employee technology compliance. In an AI study conducted by PwC, the potential contribution to the global economy from AI by 2030 is expected to be $15.7 trillion. The greatest economic gains from AI will be concentrated in a few key areas including North America (14.5% boost); the equivalence totaling $10.7 trillion (about $33,000 per person in the US).

3 Steps to Build an AI Foundation

Building a successful AI strategy starts with a solid foundation. For this, you will need three things:

Quality Data

Data is the DNA of AI. From the inception, strategic planning must include access to quality data. To avoid issues later, data sources should be compliant with rules and regulations within your territory.

The quality of your data set can be analyzed based on 6 dimensions:

• Accuracy
  • Data values are correct

• Completeness
  • Data has the expected and required values

• Consistency
  • In a data set, the same value does not change

• Timeliness
  • Data is up to date

• Uniqueness
  • No duplication of data

• Validity
  • Data value matches what it represents

AI Talent

The success of an AI campaign hinges on your AI talent. The list below provides insights into what qualities your AI talent must possess to be successful:

• Specialized skills
  • Training and experience in artificial intelligence and machine learning

• Analytical thinking
  • The ability to solve complex problems with logic and reasoning

• Creativity
  • AI requires new ways of thinking, which means creativity is an essential skill for engineers in this field

• Commitment to lifelong learning
  • Artificial intelligence technology is always evolving, so the continued pursuit of knowledge is necessary

Hiring professional AI engineers is the optimal course of action. However, onboarding new employees isn’t always in the realm of possibility due to budget restrictions and the global shortage of skilled workers. In that case, existing knowledge workers would need to be upskilled in AI. While this is possible to start laying the groundwork for AI, it also puts organizations in a vulnerable position for many reasons:

• Gaps are created in previous positions
• Learning curves are lengthy, resulting in longer time-to-market for an AI strategy
• Possibility of current employees never obtain the knowledge necessary to carry out an AI strategy

A compromise would be to take a hybrid approach with your AI skills gaps: hire a few AI engineers to manage the AI strategy while also training current employees on some basic AI engineering practices.

Getting Organization-Wide Buy-In

According to results from McKinsey’s global survey on AI, good overall leadership is a common characteristic of successful AI implementations. Getting support across all levels of management will improve the effectiveness of the AI strategy.

With AI, the key to getting organizational buy-in is to:

• Calculate ROI
• Present the positive impacts of AI initiatives
• Implement smaller projects first to gain momentum (larger AI projects can be slow to yield results)

Goals need to be measurable and the timeline for implementation fully recognized. With your audience having an unclouded vision and understanding the purpose for the project, the path to getting organizational buy-in may be smoother.

Results that AI delivers are susceptible to some degree of error. A realistic challenge of AI will always be to manage expectations. Delivering clarity of benefits and an understanding of capabilities to the team from the onset improves the chances of implementation.

Getting as many teams as possible involved in the project serves a dual purpose. First, it allows the AI implementation to run more smoothly and secondly, it will create a bandwagon effect on other team members.

Even after communicating benefits, goals, expectations, ROI, and gaining support from other team members, department heads can still have their doubts about AI. Enlisting help from the AI vendor can improve your chance of buy-in. Often, the AI vendor can offer valuable insight, real success stories, and answer tough questions.

Laying Your AI Foundation Brick by Brick

Companies continue to invest in AI solutions, as AI can be seen as the digital key to gaining a competitive advantage. But in order for an AI strategy to reach its full potential, it must have a sturdy foundation. Access to quality data, securing the proper AI talent, and garnering support from key stakeholders will ensure your AI strategy won’t buckle under pressure. A transition to AI can present problems for many organizations, however with the right processes in place, the chances for success are exponential.

To start building your AI foundation, check out Apexon’s Advanced Analytics and AI/ML Services or get in touch directly using the form below.

Also read: Strategic Technology Decisions in AI Deployment: Navigating the Path to Success