About ArtificialIntelligenceB2B
The breakthrough moment for artificial intelligence technologies in business is now. Artificial intelligence development has advanced far ahead from its earliest incarnations, and new developments in AI make it more accessible and affordable for a larger number of B2B businesses than ever before. As AI deep learning applications proliferate in B2B companies, businesses will be able to better take advantage of their growing big data to improve business intelligence, make better decisions, increase efficiency, promote productivity, and reduce operational costs. From ERP and CRM platforms to advanced eCommerce, business intelligence, personalized websites, automated social media and email marketing, virtual digital assistants, and more, the impact of artificial intelligence on B2B businesses will help drive gains for companies and their customers and clients alike.
ArtificialIntelligenceB2B.com is an AI software development company that is focused on creating custom artificial intelligence solutions that are more affordable and accessible for a wider range of companies in the business-to-business sector, from manufacturing, building and construction, security and defense, and utilities, to accounting, information technology, real estate, fintech, insurance, and more. Founded as a division of the experienced software development company DDA, ArtificialIntelligenceB2B.com boasts a 25+ year history of continuous innovation in interactive software design and development for businesses and organizations of all kinds. ArtificialIntelligenceB2B.com is ready to apply its extensive experience with comprehensive, data-driven interactive software to the design and development of custom artificial intelligence solutions that meet the particular needs of each client while remaining affordable.
Introduction to Artificial Intelligence Technologies in Business
AI got its start in manufacturing, being used in the first robotics systems used in assembly line manufacturing, using basic computer vision and movement algorithms to implement repetitive and predictable tasks within a controlled environment. The current generation of AI is focused on machine learning. Data grouping and classification, pattern recognition, probability analysis, and decision-making are all made possible by the ability of machine learning to produce human-like analytical processes. AI applications with machine learning are unique in their information processing potential in that they are capable of acquiring information during functioning and improving output over time based on observable performance. This is particularly crucial to improving AI performance when applications handle deep and complex datasets in which variables are multidimensional and often unstructured. The capacity for AI to improve over time allows it to offer insights into even the most challenging sources of information.
Deep Learning Applications in Business-to-Business
AI machine learning can be developed along either supervised or unsupervised learning approaches. When objectives are clearly defined and the AI application must classify and make decisions that meet a specified and measurable quality, supervised learning is used. In the supervised learning AI development process, the AI application is fed large quantities of labeled information, and then is given large quantities of unlabeled information. Human beings then review the artificial intelligence application's accuracy in labeling the unlabeled data set and adjust the AI parameters to improve future results going forward. This is common in computer vision applications, where AI is required to correctly identify objects based on prior labeled image inputs. Insurance claims review can likewise be refined using the supervised learning AI development strategy.
When objectives are broader and less defined, unsupervised learning is called for. This is particularly beneficial when data sets are very large and complex, which would make human-directed research too time-consuming to be practical. Examples could include AI logistics applications that analyze myriad potential routes for delivering multiple packages to multiple locations in succession and determining which is most advantageous. ERP software may also be able to determine how a combination of subtle factors in a manufacturing plant may contribute to productivity rising or falling. Unsupervised learning may also be beneficial in AI business intelligence (BI) analytics applications, where a variety of patterns may be detected that give companies an edge in insight in their specific market. However used, deep learning AI systems maximize the potential represented by big data to create high quality analytics and greater personalization for end users of all kinds.
Examples of AI for Business-to-Business
Artificial intelligence solutions will help make the most of the ever-expanding data collected by businesses. With AI applications, more information can be leveraged to produce actionable business intelligence, automate work processes, improve efficiencies, personalize end user experiences, and increase productivity. Make sure your business takes advantage of the competitive edge offered by artificial intelligence software development. To learn more about how ArtificialIntelligenceB2B.com can create custom AI applications that benefit your business, contact ArtificialIntelligenceB2B.com today.
