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Jason Feintuch Helps Answer if AI Can Generate a Successful Corporate Strategy?

Artificial Intelligence (AI) has taken almost every sector out there by a storm. The most complex of all tasks is now simplified by artificial intelligence, delivering excellent results. AI has now also ventured into the corporate world – and automating corporate strategies is the next big thing.

But the question is – can AI be used to generate a successful corporate strategy? Can it help address the dynamic requirements of the corporate world? New York financial director Jason Feintuch provides insight that may be beneficial.

Artificial Intelligence is more of data gathering, programming, and mathematics. It takes a lot of effort to curate with AI strategies, irrespective of the application. For automating corporate strategies, too, AI strategists need to consider different aspects such as the nature of the business, expectations of the business owners, as well as the existing trends in the workflow of the business. With the involvement of these and so many other aspects, AI strategies for the corporate may not even be successful in the first go, but with time and a lot of effort, the initial hiccups can always be overcome.

With a flexible approach, many corporate requirements such as credit risk models, customer segmentation, legislative risk models, trading algorithms, recommender segments, and a lot many important tasks in the corporate world are now automated with the help of AI.

AI has gone a step ahead and is now also being looked up to as an important tool to serve the management of organizations. AI-based tools help with forecasting and decision making, which explains why they are currently trending in the corporate world.

While AI has been around in the corporate world for a long time now, it is time to take it a notch higher. Financial expert Jason Feintuch states that we can now expect AI to creep into key corporate strategy discussions, too. Of course, this comes with its set of challenges as well, which include dataset handling tools, automated machine learning, and interpretability. Let’s have a look at each of these issues:

Dataset Handling Tools

Handling datasets with minimal human intervention is one of the major issues AI grapples with. But with modern solutions, prebuilt-datasets and models are readily available. These datasets can then be put to use to create strategies in different sectors.

Automated Machine Learning

Building machine learning models currently requires a range of experts through the entire process – this includes machine learning engineers, development engineers, as well as data scientists. With automated machine learning, the process will be seamless. Most of these profiles would not be a part of the process at all, minimizing human intervention.


This is another roadblock that hinders the application of AI in different sectors. Humans need to understand the core of how AI functions, how it learns from the data, how it thinks, and how it makes decisions. Currently, AI researchers are working to address these interpretability issues to make AI more easily understandable and applicable.

We definitely cannot wait until each of these problems is resolved to continue building better, effective, and seamless AI strategies. Rather, we need to look for ways and means to try and incorporate AI strategies to enhance the business workflow. It’s not long before AI strategies are going to be increasingly common in corporate strategies.

Summing Up

AI is currently helping organizations understand how to combine human and machine intelligence to get the best of both worlds. Research, analysis, and ultimately, the application is key for the successful implementation of any AI strategy. Seeking assistance from AI experts, such as Jason Feintuch can definitely help revolutionize your organization by implementing apt AI corporate strategies. You can learn more about Jason here.

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