Rapid technological advances in digitization and data and analytics have been reshaping the business landscape, supercharging performance, and enabling the emergence of new business innovations and new forms of competition.

For 10 years the prevailing trend in business intelligence (BI) and analytics has been the move toward self service. That’s about to change. In 2018 and beyond, we’ll see a growing list of what many call “smart” capabilities powered by machine learning (ML) and artificial intelligence (AI). These features are sure to help us move beyond the limits of the self-service era. we’re already starting to see smart capabilities in five areas: Data prep, discovery, analysis, prediction, and AI-powered prescriptive applications. A new Forrester Research report, predicts that in 2018 enterprises will finally move beyond the hype to recognize that AI requires hard work—planning, deploying, and governing it correctly.

Opportunities available now

Leading companies are using their capabilities not only to improve their core operations but also to launch entirely new business models. The network effects of digital platforms are creating a winner-take-most dynamic in some markets. Yet while the volume of available data has grown exponentially in recent years, most companies are capturing only a fraction of the potential value in terms of revenue and profit gains. Disruptive data-driven models and capabilities are reshaping some industries, and could transform many more.

One of the most powerful uses is micro-segmentation based on behavioral characteristics of individuals. This is changing the fundamentals of competition in many sectors, including education, travel and leisure, media, retail, and advertising.

Next wave of opportunity

Coming over the horizon is a new wave of opportunity related to the use of robotics, machine learning, and AI. Companies that deploy automation technologies can realize substantial performance gains and take the lead in their industries, even as their efforts contribute to economy-level increases in productivity. Recent advances in robotics, machine learning, and AI are pushing the frontier of what machines are capable of doing in all facets of business and the economy. The idea of AI is not new, but the pace of recent breakthroughs is. Three factors are driving this acceleration:

  • Machine-learning algorithms have progressed in recent years, especially through the development of deep learning and reinforcement-learning techniques based on neural networks
  • Computing capacity has become available to train larger and more complex models much faster.
  • Massive amounts of data that can be used to train machine learning models are being generated.

AI will erase the boundaries between structured and unstructured data-based insights

The number of global survey respondents at enterprises with more than 100 terabytes of unstructured data has doubled since 2016. However, because older-generation text analytics platforms are so complex, only 32% of companies have successfully analyzed text data, and even fewer are analyzing other unstructured sources. This is about to change, as deep learning has made analyzing this type of data more accurate and scalable.

50% of enterprises will adopt a cloud-first strategy for big data analytics.

Forrester expects 50% of enterprises to embrace a public-cloud-first policy in 2018 for data, big data, and analytics, as they look for more control over costs and more flexibility than on-premises software can deliver.

Now and Future of Analytics, AI, and Automation

You May Also Like

Leave a Reply

Your email address will not be published. Required fields are marked *