Every Data-Driven Business Needs AI Now More Than Ever
Saima Shafiq, head of applied artificial intelligence transformation at PNC
Saima Shafiq, head of applied artificial intelligence transformation at PNC
As a head of applied artificial intelligence transformation at PNC, Saima Shafiq is in charge of identifying the most promising prospects across business operations and departments in order to support transformation and use of artificial intelligence technology to serve customers and employees. Her day begins with an analysis of operations' present state and identification of those operations' existing state processes. She then develops a plan to assist teams in enhancing their day-to-day operations by implementing business artificial intelligence.
What are the most recent trends that you are seeing in the space that are changing the entire industry today?Although artificial intelligence has been available for more than a decade, vendor products for technology solutions that applied AI have evolved and matured quickly in recent years. Businesses that once considered investing in testing out AI technologies to make a point are now significantly investing in expanding the usage of AI technology. As a result, now is the ideal time for businesses to begin reaping the rewards of implementing AI technology. The tools have improved, as have the partners in business and technology.
What are the challenges that the industry's leaders face?
There are numerous challenges that industry is facing currently. For instance, we could look at the obstacles in last few years and determine whether a potential recession was approaching. We could also confirm that investments were made wisely based on priorities, real-world efficiencies, and the prospective return on investment. Hence, the difficulties of this year are more focused on being ready for the recession and focusing our tech investments for automation so that we are not only fixing smaller issues. We're tackling bigger issues that could keep us adaptable and prepared to provide greater output that are considered coming ahead. Businesses are putting plans in place for it just like every other financial institution.
The second difficulty is the ability to set priorities. When there is a deliberate effort to apply AI wherever it fits, there are nearly a limitless number of opportunities waiting to be taken advantage of. There are lot of areas where automation is possible, but the biggest challenge for the leaders position is identifying the bigger buckets, investments with the highest returns, the most strategic types of areas to spend their time, and requesting business commitment to understand the processes where automation should be implemented.
Because many times people talk about automation efficiency in terms of the return on investment or the amount of time it would save, I would emphasize being able to recognize the impact. How much volume could be process? How many employees could this automation support? But to be honest, this is not the best test. The business results that go beyond merely saving time for employees are what should be included in the better measure. Business outcomes should take into account time savings, but they should also take into account things like improved customer or staff experiences, the capacity to provide more specialized, individualized services for our clients, and increased employee motivation.
The business results that go beyond merely saving time for employees are what should be included in the better measure.
If we alter the course of events that have been occurring for years, it will happen again. Everyone finds adjustment difficult, but it should be viewed as a chance. Also, persons who have been a part of those groups for a long time are accustomed to doing things the traditional and legacy manner. For them, the idea that things might change might be unsettling. Some will consider this as job loss but some might believe get the newer tools to work on I can improve my skills so that I can use my knowledge to complete more valuable tasks. In light of all of that, I believe that the mindset of those in charge of operations is another significant obstacle that makes it difficult to decide precisely what should be automated.
What would be your single piece of advice for the existing and upcoming professionals in the field?
I would advise technology leaders to have a deeper understanding of the business issue than ever before. It cannot be just because they are computer savvy that they are providing value or that they can have automation provide some boost. Since they are willing to learn about the business process, at least at a level deep enough to understand the process' ultimate purpose, it must originate in their brains. The value can only be provided if they identify the ultimate goal, the ultimate business outcome that business teams desire from any process, any product, or any solution that they have. Sometimes people just look at the process and try to tackle that problem. Hence, the only way to resolve this or overcome the difficulty is to remain by their side, gain their confidence, credibility, and understanding present opportunities after they have exercised the appropriate level of due diligence.
It will be too late if businesses do not priorities or invest in using artificial intelligence. It seems that individuals who are ahead of the curve are already developing quickly. Yet, it won't suffice if certain organizations continue to believe that I'm just looking at a tool or an issue. We must implement it broadly.
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