Everyone talks about AI, but what is it really? Source: Shutterstock

Everyone talks about AI, but what is it really? Source: Shutterstock

A smarter guide to AI for CXOs and SME leaders

ORGANIZATIONS have been obsessed with artificial intelligence (AI) for the past 18 to 24 months, believing it can provide them with a strong competitive advantage and a key differentiator in a crowded marketplace.

As a result, the world has spent nearly US$24 billion on AI and cognitive technologies — and forecasts suggest that spending will reach US$77.6 billion by 2022, growing at a CAGR of 37.3 percent between 2017 and 2022.

Obviously, with all the attention and investment in AI, you tend to think that executives would have a clear idea of what AI really is. A new report suggests, however, that most executives don’t.

AI is not one technology

AI is a disruptive technology because it has the potential to boost efficiencies and cut down costs almost overnight. However, AI is often misunderstood, which is why leaders fail to get the most out of it.

SME leaders and CXOs need to understand one thing about AI. It’s not one technology. AI is a bundle of technologies that run on algorithms and data.

Some of the technologies that AI is comprised of include computer vision, speech recognition, autonomics, neural networks, machine learning, image recognition, natural language processing, deep learning, and virtual agents.

According to experts quoted in the report, businesses are working on pilot projects and proofs of concept (PoCs) but since they’re using a piecemeal, isolated approach, they’re struggling to unleash the true potential of AI.

However, as soon as leaders understand that AI is not one technology, it brings clarity in three areas for the business:

# 1 | Stop looking for AI professionals in the market

When you realize that AI is made up of many technologies, you realize that it’s a world of its own. Programmers, for example, who know one language, may not know any other. Similarly, machine learning experts might not know much about chatbots or virtual agents.

Hence, when companies look for talent to support their AI projects and build AI capabilities, they must take the time to understand the underlying requirements for each of the specialties they need for their business, define an appropriate job role, and then look for the right talent to support their growth.

# 2 | Every business process could use some aspect of AI

Every part of a business, every function and process, can use AI in one way or another. Things as diverse as digital marketing and finance could use different components of AI, and in many cases, could do so right out of the box when they invest in a solution that is right for them.

However, it is also true that attempting to adapt AI into every business function would mean running too many pilot projects — which could strain the organization’s resources.

As a result, companies must work on identifying all the areas that could benefit from AI, map out what kind of AI they need, and then prioritize each depending on the time and resources that would have to be invested as against the benefit that it would provide.

# 3 | Technology works best when combined and integrated

Accenture recently published a report that explained why it’s important for businesses to think about making the most of the technologies that they’re using by combining them instead of working with each in isolation.

Analysts at the company emphasized that businesses must focus on distributed ledgers, AI, extended reality (XR), and quantum computing — a stack they call DARQ.

The general direction, however, is for companies to identify what works best for them and then move on to understanding what they really need to help the business climb the digital maturity curve.

At the end of the day, just because organizations are able to find the budgets to invest in new and emerging technologies.

The starter guide to AI success

Understanding what AI is and some fundamentals of how it could help companies not only helps set the record straight but also ensures executives have the right frame of mind when brainstorming ideas for new applications.

However, before plunging headfirst into new AI projects, CXOs and SME leaders need to delve deeper into what their business needs before they can leverage AI to create solutions.

According to the report, there are four key steps that must be followed in order to ensure success:

# 1 | Don’t forget the “why”

“For every moment spent trying to execute on the how of getting digital transformation done, the approach should tie back to the why and what business value you are trying to drive.”

Essentially, organizations that are keen on developing AI capabilities and leveraging it to get ahead of the competition might spread themselves too thin and take up too many projects.

Experts warn against that and suggest focusing on a handful of projects that are tightly tied to business and customer outcomes rather than vague possibilities.

# 2 | There is no AI without data

AI only works when organizations have access to data that is relevant to their businesses.

Organizations can either procure data from external sources such as Bloomberg or other vendors, collaborate with supply chain partners and business stakeholders, or use internal data from its repositories.

The general rule is, the more (relevant) data that an AI model has, the better its results. Hence, before thinking about investing resources in smart AI solutions, the organization must check if it has all the data it needs to produce meaningful results and insights.

# 3 | Avoid AI tourism

“AI is cool and PoCs are on the rise, but many of them never reach the pilot or production phase because they are not focused on solving critical business issues, do not have senior executive support or have no plan for scaling. This is called ‘AI tourism'”.

Obviously, experts cannot emphasize enough, the importance of prioritizing AI projects based on business needs and executive support.

A brilliant AI project in the finance department is less valuable than an average project in another department if the former isn’t aligned with the needs of the organization and doesn’t have the support of business leaders. The true value of AI can only be harnessed with a solution is scaled across the enterprise.

# 4 | Change heads, hearts, and hands

“AI requires talent that understands the intersection of data and algorithms, as well as their impact on process chains and workflows.”

In the report, experts recommend that CXOs and SME leaders collaborate with experienced partners and vendors who have the know-how to not only provide an AI solution that is fit for purpose but also the ability to drive a transformation within the organization’s culture.

In order to thrive in an AI-first marketplace, organizations need to change how they think, do, and act, and the expertise of specialists — the report emphasizes — will help conserve resources and maximize returns for the organization.