Are we ready for Artificial intelligence in the business landscape?

Creating an effective strategy for AI development

Whether your company is in the field of retail, utilities, healthcare, media, or logistics, the bet is that artificial intelligence (AI) is already touching your industry, even if you aren’t aware of it. There are endless possibilities for what AI can do for your business. Just to name a few, some of the common use cases for which it’s being applied are fraud detection, smarter services, research insight, demand forecasting, patient diagnosis, inventory optimization, recommendation systems for e-commerce, and the list goes on.

According to the research “Reshaping Business with Artificial Intelligence” by MIT Sloan Management Review and The Boston Consulting Group, in a global survey of more than 3,000 executives, managers, and analysts across industries, almost 85% believe AI will allow their companies to obtain or sustain a competitive advantage. Nevertheless, only one in 20 companies have extensively incorporated AI in offerings or processes and less than 39% of all companies have an AI strategy in place. Even from the largest companies (with at least 100,000 employees) that are the most likely to have an AI strategy, only half have one.

As AI tech continues to progress at a dangerously fast speed, company leaders need to step it up and develop an AI strategy that fits into their business model. We will list 4 steps companies need to go through to create an effective strategy for AI development.

1. Identify in what areas AI will have more impact on your industry

How AI it’s going to disrupt your industry? What may look like a threat can be turned into an opportunity and even a competitive advantage if you manage to get ahead of your competitors. A recent study conducted by Nils O. Fonstad, a research scientist with the MIT Center for Information Systems Research, suggested that the most successful companies of the sample where practicing digital innovation to some degree in four areas (simultaneously):

• Employee experience
• Business operations
• Customer-facing products and experiences
• New business models

Instead of focusing your AI objectives in replicating humans, think about how AI-enabled technologies can support processes, increase accuracy and improve experiences. Sometimes AI can give you the answer instead of being the answer itself. For example, using AI to analyze the content of client calls through voice recognition can identify common ground between all of the calls to get actionable insights and therefore improve customer service. In this case, AI is needed valuable because a human wouldn’t be able to record, analyze and draw the same conclusions in an efficient manner.

2. Align strategic goals with AI initiatives

AI initiatives are not supposed to be isolated from the rest of the company, they imply an organizational and cultural change and for that matter, they should be aligned with strategic company goals. Adopting AI at scale can completely change the corporate strategies. This is a decision that comes from above. Building a business case for AI initiatives will help everyone get on board while having senior leadership committed with the idea is essential to allocate resources, align the organization towards achieving the objectives and have impactful results.

Managing AI technology is not a “business as usual” kind of thing. As well as commitment, some structural changes will need to be made. A good example of this is creating cross-functional management teams to discuss and redefine their processes.

3. Get your data together

AI algorithms aren’t natively smart. Data for an AI algorithm is like nutrients for a kid. It has to “ingest” and analyze data to learn and become intelligent. Start thinking in building a repository to store raw data in its native format so that it can then be analyzed.

The development of AI relies on huge amounts of data (“big data”, for that matter); otherwise, it will lack accuracy. AI needs real-time access to large amounts of high-quality data. Data can come from many different sources and formats: internal data sources, such as sales or purchase data; external sources, such as social media or providers; sensor-generated data (from manufacturing lines, retail environments, etc) and it can either be structured or unstructured. A robust data infrastructure to integrate data into an automated work process is needed to provide data access throughout the company and creating the right environment for AI initiatives.

4. Acquire analytic capabilities

In a survey conducted by MIT Sloan, executives gave several reasons for not adopting AI. 21% cited the scarcity of AI-related human capabilities — and these same executives were 50% more likely to also say that AI presented an uncertain business case, suggesting that human capabilities are critically important to capture the returns from AI in new organizations.

Looking into the future, data science and quantitative methods will become transversal job functions instead of being a concentrated role of a specific person or department. We are talking about entry-level analyst executing machine learning and cross-validation all by themselves. We are already seeing a gradual evolution in the job market towards jobs requiring computer sciences skills.

Acquiring analytics capabilities and hiring AI talent will build a solid ground for the future. This is not an easy job, filling technical positions can be a time-consuming and expensive task due to the lack of skilled professionals trained to cover technical job positions and a high demand for them. You may have to rethink your recruitment process and employee experience strategy to fill positions of this high demand jobs.

Last but not least

Odds are your company isn’t behind, yet. Start by aligning strategic goals with AI initiatives and be faster than your competitors in evolving towards a changing market. It is far more important to create the instances for your company to become flexible and adapt quickly to market needs than to focus on a one-time only investment that is going to reduce costs or increase productivity. AI technology will evolve fast, so become quick enough to be able to take on AI opportunities as they come.

About our studio

At 8wires we help companies make data-driven decisions and become digital leaders by leveraging from the opportunities of technology. From strategy to digital tools to digest, analyze and visualize actionable information, we can guide you through the whole process.