Artificial Intelligence has been all the buzz this past year with more and more advances in technology making the implementation of a successful AI business strategy a necessity.
Companies everywhere are trying to capture the value of this new emerging area, but with AI being such a complex and broad topic, how does a business create a strategy for the future that includes Artificial Intelligence?
We at Seamgen have some of the world’s leading AI scientists that have the capabilities of providing top-of-the-line solutions to meet our clients’ business needs, and furthermore we want to help others create a successful AI business strategy for the future.
Turning AI into Business Solutions
Before implementing AI, it’s important to understand what exactly artificial intelligence can mean for you. Taking a step back and determining the overall picture is important to figuring out how a company can turn AI into valuable business solutions.
Artificial Intelligence includes a broad range of differing technologies that learn over time as they are exposed to more data. As the technologies collect the data, they are able to analyze the information collected and make informed decisions based on the analyzed data. Once this process is done, the technologies are learning from what they have already analyzed to better improve their decision-making process.
With AI having such broad capabilities, where does it fit into one’s organization?
It is easy to get lost with the many differing AI technologies, but it is an important first step to identify the areas within one’s own organization where AI can create the most significant long-term change and advantage. Once these areas are identified, the next step is determining whether it is a plausible opportunity to implement AI.
Often times it can be easier for organizations to look at low-hanging fruit, such as managing risk or forecasting for the future. The low-hanging fruit allows for your organization to quickly implement AI, which will give you a better advantage in the long-run. Once these are accomplished, organizations can look to sophisticated solutions.
Executing an AI Business Strategy
To determine your AI business strategy, many experts say that it comes down to a two-part criteria test. The first part of the test is evaluating the complexity of the work.
The work and development could be predictable and routine like, but it can become complicated when the technology requires the application of human judgement. For example creating software development centered around quality assurance still needs human research to define the type of quality they are looking for. While it is still possible to create Artificial Intelligence around quality assurance, it will create the work more complicated for the AI scientists.
Once the complexity of the work is determined, the second part of the two-part criteria test is evaluating the intricacy of the data. Low-complexity data is structured and low volume such as budget information or sales data, whereas more complicated data can be unstructured, volatile and high volume. Developing an AI solution with high complexity data involves more time and higher expertise from your AI scientists. Often times, it is hard to find a dedicated team with high-levels of expertise to develop more intricate AI solutions.
For example, our scientists developed a system for predicting dangerous conditions in space for NASA. It was no easy task as the data came from different sources, contained numerous variables and was based on a volatile frequency of events. Luckily, we had the expertise to solve the issue at hand by applying a proprietary time series analysis technique allowing for 90% accuracy through the AI solution.
After evaluating both the complexity of the work and data, an organization will have a better idea of the scope of the AI project they wish to implement. With the right data, resources, and people, a company can follow an agile development cycle to properly fit their business needs for the future.
Need Help on Implement AI?
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