This article is originally posted at Tenfold.com. Technology trends will influence not only big companies but also small and medium-sized businesses. In 2018, there is a lot to expect regarding machine learning and automation. It is said, that the machine learning market will possibly grow by about $7 billion from 2017 to 2022. Not long ago a machine was able to finish a math exam faster than an average human.
Data Science and Machine Learning are growing at a rapid pace as more and more companies, whether it is large or small, are seeking to expand their arms. But the primary adopters and implementers of these technologies today are majorly large enterprises and smaller businesses, because big organizations have much capital to invest, while smaller ones are unencumbered by long chains of command. On the other hand, medium-sized enterprises are facing or having a harder time. As having not much resources like the bigger players or the agility like the smaller ones, mid-sized businesses are slower to adopt and implement data science and machine learning technologies. However, they need a smart approach in their efforts and if it happens, they can get the significant value of where they do invest.
As AI use and innovation continue to increase globally, getting small and medium-size AI companies more involved in the financially lucrative and still-nascent AI revolution is a developing goal of the US government. One federal agency, the National Security Commission on Artificial Intelligence (NSCAI), is asking smaller AI vendors to send in comments and suggestions by Oct. 23 about how to make it easier for them to work with the US government to bolster commercial AI innovation. With the comment deadline looming, the NSCAI says it seeks detailed input from small- and medium-sized AI vendors, particularly when it comes to working together to catalyze AI development, expand the national security innovation base, and make it easier for them to do business with the federal government. The agency says it is specifically seeking recommendations involving needed statutes, regulations, policies, budgets, organizations, and cultures, as well as other related issues. The NSCAI's appeal for comments and input from smaller AI vendors was published Sept. 23 in The Federal Register.
With each passing year, the fintech sector is providing faster, flexible and secured consumer experience, and is protecting against the risks and vulnerabilities of traditional insurance and loans. In fact, the global fintech market size is expected to grow to $124.3 billion by the end of 2025 at a CAGR of 23.8%. With a vision of providing small and medium-sized growth companies with debt finance, along with aiding them in competing against the large corporations, UK-based OakNorth is utilising artificial intelligence and machine learning to fulfil the dream. Since its inception, OakNorth has secured over $1 billion from leading investors which has been used to launch lending operations and others such. After meeting each other at college in the year 2002, Khosla and Perlman decided to launch their own business that could solve the challenges they had to face in securing debt finance from high street banks during their previous business -- Copal Amba which scaled to 3,000 employees and was later acquired by Moody's Corporation in 2014.
Businesses should start small and fail fast with machine learning (ML) projects to get the best ROI. Some of the most common use cases for small- to medium-sized businesses (SMBs) include fraud detection, sales optimization, marketing, and document analysis. But the benefits of implementing ML goes even further. This ebook, based on the latest ZDNet / TechRepublic special feature, helps small and medium-sized businesses build a technology stack that promotes innovation and enables growth. Steve Tycast, director of data and analytics at AIM Consulting, said ML efforts focused on operational analytics can reduce costs, drive efficiencies, and increase speed to market.