US falling behind in AI, ML

According to Forbes magazine 80% of enterprises already have some form of AI (artificial intelligence, machine learning, data analytics) initiatives with Asia Pac leading the field.Product Innovation and Research & Development,Data engineering, Intelligent workflow and decisioning automation, and analytic operations at scale being main areas for AI.

In many of the areas, US is behind both AsiaPac and Europe which is concerning given that traditionally US has lead the way in emerging technologies.

AI and ML planning

State of Affairs

The three main points from Forbes article https://www.forbes.com/sites/louiscolumbus/2017/10/16/80-of-enterprises-are-investing-in-ai-today/ are:

• 80% of enterprises already have some form of AI (machine learning, deep learning) in production today.
• 30% of enterprises are planning on expanding their AI investments over the next 36 months.
• 62% expect to hire a Chief AI Officer in the future.

An interesting insight from the article is that enterprises are starting to benefit from AI like never before. More enterprises benefiting would mean more and widespread application of AI techniques.

What can we do?

However, the fundamental question (like always) – is it vaporware? And when is the right time to jump in? And what can we do to establish US dominance in such emerging fields.

We at Sunvera started working on AI (machine learning/data-analytics) three years ago when we developed a product for a client in the financial sector. The AI web portal was designed to accurately forecast macro-economic metrics for application in financial investments to maximize returns and minimize losses. The system uses historic macro economic indicators to derive near future and long-term forecasts.

The mean error between actual and forecast values was less than 0.25% indicating a high confidence factor in results.

Our experience developing the product has helped us understand the nuances not only from a software development point of view but also from client’s application of AI to their businesses.

For example: in any application involving Artificial Intelligence, Machine learning or data analytics, it is important to start with good and sufficient data. It is also important to have wider datasets – factors not directly affecting outcome – to ensure good results. Finally, determining how to present results – web portal, mobile apps – is important ensure clients are able to benefit from the application.

At Sunvera Software we we can help you navigate and benefit from AI, ML and data-analytics. We know to separate vaporware from real when it comes to your specific solutions and help increase revenues and reduce losses.