Millions of dollars in venture capital or acquisition costs come at a price: Executives need artificial intelligence to begin delivering on its promises of increased worker efficiency and product innovation. But if checks are signed too quickly, companies may not find the ROI they would expect waiting for them at the end of the process. PwC analysts recommend AI technologies must first be evaluated by a diverse team of experts who can attest to the technical backbone of the company, asses if the needed data sources can be improved over time, and determine if AI systems can applied to a company's unique business model. "Moreover, integration plans should consider responsible AI principles and practices to extract a deal's value well after it closes," the report states. A laser-tight focus on business objectives can help maximize ROI for companies when it comes to AI initiatives.

Intelligent automation, like RPA (robotic process automation), natural language processing and virtual agents, can help you improve efficiency and productivity in many ways. Self-learning processes can help you empower employees, strengthen customer relationships and open new ways to innovate. You may have found success by applying automation ad hoc, but most companies haven't been able to scale these benefits across the enterprise. Whether due to a lack of skilled talent or a clear vision from the top, automation investments are proliferating without ever reaching their true potential. To succeed, you need an enterprise-wide approach.

Global management firm Boston Consulting Group has just employed a'digital human' as an advisor to its internal teams. 'Miku' the digital employee under training, however, had her first public interaction on stage. This was at the recent IBM THINK in Sydney, where BCG managing director Miguel Carrasco showed how Miku is working with BCG's PTO (Predictability, Teaming and Openness) facilitators. "I help the PTO coaches to support teams by giving advice on work-life balance issues and sharing our top tips on project management," explains Miku. She then asks Carrasco, "Speaking of which, have you had a busy week? I can set up a few reminders on your calendar to prioritise some downtime."

Today, everyone's talking about Artificial Intelligence (AI) and how it's going to change the way we conduct business, and live our lives, forever. In fact, it's shaping up to be the single biggest technology revolution the world has ever seen. Private investment is booming, as companies continue to scale and industrialize their AI applications. A new cohort of AI-first businesses is flowing into the market, shifting the competitive landscape for incumbents. And as many as three-quarters of executives say that some kind of AI will be actively implemented in their organization within three years.

There are exciting advancements in process automation and robotics technologies which have resulted in an ever-growing interest in – and need for – Robotics Process Automation (RPA). Robotics has been very successful in industrial and manufacturing industries for some time. The advancements that can impact back-office uses today are many, and can represent a good ROI. But when we think of robots, what comes to mind? The Hollywood references are endless: I, Robot, WALL-E, Transformers, Data from Star Trek: TNG, Ash from Alien, or even The Jestsons' maid. But, without a clear understanding, how can we determine how it can help?

In my previous blog, I looked at the frustrations that many citizens experience when dealing with automated services. Chatbots frequently can't provide the answer that people want and are unable to escalate an enquiry to a human agent that can help. But as technology, notably AI, continues to improve, organizations in the public sector have the opportunity to create next-generation chatbots that will be able to offer citizens much more rewarding interactions. Today, only five percent of customer interactions with contact centers globally are powered by AI technologies, but Gartner estimates that by 2021 this will rise to nearly one in six. Fortunately, government agencies have access to a new generation of AI-enabled chatbots, capable of detecting caller intent and responding to the root causes of customer inquiries, considerably reducing call volumes. Customers can signal the same intent in many different ways.

There are more than four billion active internet users globally, thereby becoming the single largest target group of potential customers for businesses. It is not surprising that businesses are trying to establish a robust online presence -- the most popular mode being through a fully-functional website. Thus, they are availing custom web development solutions from expert developers. Such is the potential of the internet that no business can afford to overlook it. Irrespective of their size, businesses are trying to make their websites more interactive.

This is a fundamental question that leaders in business and academia are grappling with, and we are only beginning to get a sense of what the enduring human skills are in this nascent phase of human and machine collaboration. Imagine that you are responsible for operations at a large manufacturer and you want to maximize the life of equipment parts while avoiding unnecessary downtime. In the past, your maintenance team relied on "tribal knowledge" estimates or doing an ongoing, in-depth analysis of each piece of equipment. Today smart factories can use machine-to-machine and machine-to-human communication with cognitive technologies to make timely, accurate decisions. This predictive maintenance raises thought-provoking questions about the role of maintenance personnel versus the role of predictive algorithms, and what kind of traits a modern-day maintenance worker should possess.

Back in late 2017, Gartner analyst Nick Heudecker estimated that the failure rate of big data projects was 85%. Move the calendar forward two years and there's no solid evidence proving that the failure rate has improved in any meaningful way. But help may be on the way. A growing number of artificial intelligence experts are arriving at the conclusion that the technology has the potential to turn big data failures into resounding success stories. The trick lies in knowing how to use AI correctly.