Here are 3 Artificial Intelligence Myths

Artificial Intelligence Myth

The hype around Artificial Intelligence/AI is substantial. It has long been a topic that has fascinated the general public, as evidenced by the 99 movies that have been made since 2001 with AI as a central part of the storyline. With such widespread interest in this topic, so too has come much misinformation. As you plan your AI strategy, be sure to understand the difference between Artificial Intelligence Myths and what is reality.

Myth #1:
AI and Machine Learning Are the Same

One of the prevailing artificial intelligence myths concerns machine learning. We spoke about this topic in an earlier post, Demystifying Artificial Intelligence vs. Machine Learning. Machine learning is one category of artificial intelligence. A Machine Learning strategy can only be done with a well-thought-out data acquisition plan. Artificial Intelligence is a much broader term that refers to several different technologies, such as Natural Language Processing and Speech Recognition.

Machine Learning has become a central part of many Artificial Intelligence strategies. As a viable approach to collecting data, this process can drive learned behaviors that become the basis for AI performance. Just remember that the relationship is one way: Machine Learning is one of many inputs that can provide the necessary data that can drive Artificial Intelligence insights.

Myth #2:
My Business Does Not Need an AI Strategy

Every business should be focused on how best to serve their market, deliver high value, and provide a unique selling proposition to their customers. These core components are part of every business strategy. But you should also have a technology strategy, especially when technology is quickly changing how businesses operate and deliver value. One example is the Cloud – how will you incorporate this technology in your IT strategy? Repercussions include how all of your applications integrate, what staffing requirements you must overcome, and how will security be managed in the future?

Similarly, companies also need an Artificial Intelligence strategy. How will you incorporate this technology into how your business operates? Will you work with partners to best leverage the potential business benefits? Or is AI so critical that you must build a staff of data scientists to apply this technology in your way, with a proprietary deployment?

Learn more on the challenge of building your Data Scientist team, Why Is There a Shortage of Data Scientists?

A great place to start is to find potential ways that you can leverage AI’s power to augment decision-making and improve the performance that can be extracted from existing business processes.

“In the next four years, 69% of what a manager currently does will be automated. In such a disruptive environment, enterprises need a reality check on how best they can integrate AI into their strategy and be ready for forthcoming disruptions.”

6 Artificial Intelligence Myths Debunked, Gartner

Myth #3:
Automated Processes Can Learn on Their Own

It is important to understand that Artificial Intelligence does not operate autonomously. Any time this technology is first implemented, a learning process must be established to gain insights on how best to understand the desired insights. But even after this process has been learned, data scientists must still be involved to determine if you are using the appropriate data sets and to remove any bias that might exist as part of the data collection process.

Over time, new variables can emerge that impact how data is collected or calculated. This transformation must be appropriately managed to ensure viable predictions can still be extracted from the AI-based process. Learning behaviors need to be refined to ensure the proper integration of new knowledge and data into the next learning cycle.

What should be clear is that the use of Artificial Intelligence as part of a business process is not as simple as just turning it on. Considerable knowledge and understanding of this technology must be applied to ensure meaningful insights and behaviors are possible post-implementation. And, over time, this process must be evaluated and understood by experts to ensure the right activity is achieved. Implementing your Artificial Intelligence strategy can be time-consuming, costly, and require substantial resources to complete. It is for this reason that many companies are instead opting to work with partners to take advantage of this exciting new technology.

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