Article 11 of 13 in Series
Many people are interested in artificial intelligence, and there are numerous tales about the incredible advancements that AI is enabling in business, medicine, and a variety of other fields. However, the stories of spectacular accomplishments obscure a crucial aspect of the AI process: the arduous work that precedes that success.
Justin Nguyen, Sense Corp.’s director of data science and AI, compares the AI triumphs to snapshot images he’s taken at the tops of some of the world’s most stunning peaks. A stunning picture is captured in one photograph, which includes a blue sky with puffy white clouds, kilometers of ocean coastline, an entire forest, and hills of rocky outcroppings. It’s breathtaking.
“You can see how gorgeous it was up there,” he remarked. There was a lot of effort put into this.” Justin Nguyen
Nguyen expressed the following. Getting to the AI Summit, According to him, AI is equivalent to that breathtaking summit photo. There is a significant amount of effort involved, as well as numerous difficulties to overcome, but you don’t hear much about those.
“Instead, you hear about all the incredible success that AI has had in all of these other businesses,” he continued. “It’s all about the hype and the anticipation. It’s something that everyone wants to do. It’s the gossip of the town. However, you don’t hear about the journey to get there. You just get a glimpse of success.”
As Nguyen pointed out, the majority of data science efforts fail. Almost all of them never see the light of day. Project failure can be attributed to three key factors.
First and foremost, there is a data issue. Data is at the heart of any successful AI program, but not every company prioritizes data quality, master data management, and data governance across the board. As a result, data may be erroneous, isolated, and slow to process.
Second, the company may not be prepared. According to Nguyen, organizations must have a clear knowledge of the requirements and competencies required for data science efforts. This includes performing extensive due diligence to identify feasible use cases.
Third, businesses must ensure that their technology stack is current and that their data pipelines and procedures are scalable. That’s what it takes to make AI initiatives genuinely operational in a company.
“The most common error I see firms make early on is choosing the wrong use cases,” Nguyen remarked. “Choosing your early use cases is critical, since it puts you up for long-term success.”
An excellent first use case is one in which the project’s worth can be measured in dollars saved, money earned, or some other metric. This first use case, according to Nguyen, puts you up for a rapid win.
“Not only does your early triumph provide that value, but it also provides you with a tangible and appealing narrative,” Nguyen added. “It brings the organization together around a common goal. It raises the level of interest. It gives you the energy you need to keep going and to push through all of these major technological and process changes.”
The next step is planning, which Nguyen believes is where many firms go wrong. To begin, convene a brainstorming session with leaders from throughout the organization to discuss options and potential problems. Then you prioritize based on the value of the business and technological feasibility. This entails analyzing the data you have and determining whether it is accessible and correct, as well as examining the technology you have in place to complete the task and taking stock of your organization’s skills and capabilities.
It may appear to be a lot of effort, but don’t let that deter you.
“Start small, be adaptable, and start early,” Nguyen advised. “Today is the first day of AI. Don’t put off starting until everything is in place and the stars are aligned. Begin with small victories and work your way up.”
This is the approach he proposes because AI is about progress, not perfection. Over time, you will learn, advance, and improve. “The earlier you start, the more improvement cycles you’ll have,” Nguyen explained.
Now is a fantastic moment to get started because artificial intelligence is gaining traction in businesses across the board, regardless of department.
“The fact is, there’s a change happening right now where a lot of people are starting to get extremely excited about AI,” Nguyen added. “They like talking about AI and hearing about it.”
This is something you can utilize to further the cause within your organization. Nguyen recommends evangelizing, educating, and enabling business users on a daily basis. As a result, stakeholders value AI development efforts and begin to recognize the significance of data quality, capture, and accessibility.
“Artificial intelligence is a team sport,” Nguyen added. “Involve and empower the rest of your company, and bring others along on your trip with you because you’ll travel further together than you could alone.”
Don’t forget to look for the rest of my Artificial Intelligence articles in my series. You can subscribe below to gain access.