Six in ten businesses believe automation will have a positive impact on businesses to help give them a competitive advantage. The majority of businesses believe that automation will increase productivity and give them a competitive advantage. That's according to research from Robert Half which found that six in ten businesses believe automation will drive productivity. Digital transformation and automation has allowed businesses to use artificial intelligence (AI) and robotics to enhance their performance on simplistic tasks to create a more efficient working environment, by helping businesses to become more efficient, productive and compete within their respective market areas. It was found that 87% of executives have already seen the positive impact that a growing reliance on technology can hold for organisations.

Companies across the globe are embracing artificial intelligence (AI) within their organizations -- 51% of firms have already implemented or are expanding their implementation of AI. An additional 20% plan to implement AI in the next 12 months.1 However, to ensure success and mitigate the risks, CIOs must take the lead and engage the lines of business on their AI initiatives, modernize IT, and ultimately drive the AI agenda. CIOs are optimally positioned to build the organization's overall AI capabilities as the data, applications, server, accelerator, fabric, and storage infrastructures that they manage are critical for driving business value with AI. However, their IT teams will need to transform.

As the amount of data increases, so does the need to manage it. With AI data management becomes much simpler to achieve business outcomes. The cloud environment has significantly changed from when it first came to market, with more options available and more capabilities including the increasing use of artificial intelligence (AI). SAP recently announced new capabilities on SAP Cloud ERP, which will help benefit businesses in the ever changing digital environment. The first focuses on increasing the level of automation based on predictiveness and machine learning in the product.

Humans and machines need to learn from each other, says Ray Wang. The will they or won't they debate surrounding robots replacing humans has caught the imagination of both business and consumer in recent times, with a myriad of reports putting forward a plethora of stats in support of the opportunity, or threat, of robots and AI. Thus, it was unsurprising that a key focus on day two of the SAP User Group Conference was on the polarising emerging technology. Ray Wang, Principal Analyst, Founder, and Chairman of Silicon Valley based Constellation Research, took to the stage to pose the topical question, 'Will Robots Take Over?' The answer put forth by Wang, unsurprisingly, was not straightforward. Yes, AI and machines will take over certain jobs, but there will always be a need for human input when it comes down to qualities such as creativity, compassion and physical presence.

AI taken to another level as IBM Watson analysis data in the sky. IBM is taking to the skies with its latest Watson deployment, with Korean Air using the AI tech to help crews on the ground with aircraft maintenance. Using machine learning, Korean Air wants to increase the safety of their planes by taking advantage of the data collection, analytical ability and AI capabilities of IBM's Watson. IBM's Watson will do this by collating data from technical guidelines, inventory and in-flight incident history to analyse a current or potential future problem. In doing so, it will help to identify the cause of these problems and quickly offer an effective solution.

SonicWall works with 18,000 partners, and CEO Bill Conner believes collaboration is central in cybersecurity. The cybersecurity industry is currently abuzz with talk of automation, principally the central role it will play in handling the mass of threats besieging organisations daily. Automation might be a current trend, but this does not mean it is an entirely new phenomenon, as some organisations have been repelling attacks with machine learning for years. One such company is internet security provider, SonicWall, and CBR spoke to the CEO of the company, Bill Conner, to gain insight on how it is taking on the threat landscape and keeping customers safe. Mr Conner said: "We have focussed on how to use software to isolate segments in your network; our firewalls have been using machine learning for over ten years. A malware cocktail is the easiest way to think of it, these three different technical engines are looking at every file that is unknown, and it is going to block that file from going in until it can characterise it and give it a green light in real time, it is all automated."

Artificial Intelligence and Machine Learning are terms that are currently filling the air in the tech world and across a range of industries, as plans for massive disruption begin to take shape. Both technologies are set to be central to the future, particularly in critical fields such as cybersecurity, and the financial services. Technology is developing at a gallop, and an ever widening skills gap is causing concern, driving the need for technology to fill in for the lack of human skills. However, it is common that the two terms are haphazardly thrown together under the banner of automation, or simply used together without distinction. Because of this, CBR is setting out to find out the main differences, what they are best applied to, and who is standing out in each of the popular spaces.

Artificial intelligence and machine learning are playing an increasing role in most aspects of enterprise technology. Because the challenges of cyber security are changing AI is playing an increasing role in defending enterprises from criminals. Malware is today evolving so fast that manual defences simply cannot keep up. Researchers at G DATA have been counting new malware types for many years. In 2007 they found 133,253 new malware specimens.

Will the new Vertica 9 platform from Micro Focus lead the way for other analytics platform providers in enhancing machine learning capabilities? Micro Focus has announced the release of Vertica 9, a new analytics platform offering enhanced machine learning capabilities. The new in-database machine learning developments are intended to simplify the creation and deployment of machine learning models, bringing on board new algorithms and data preparation functions. In addition to this, continuous end-to-end workflows and model replication are also new features included in Vertica 9 to achieve this goal. New support for the Google Cloud Platform will enhance the user's freedom, while scalability and performance have also been targeted.

Would you trust a robot to tell you how to vote? Scientists from Kimera Systems have developed a robot that will be able to help users make political decisions. The robot named'Nigel' uses artificial intelligence (AI) to become aware of its user's life and utilise the information by offering advice to user's including how to vote. Unlike other AI robots Nigel programmes itself as it goes, rather than teach itself how to perform and effectively carry out tasks. It works solely on how the user is themselves, for example if they offer traits of a left wing supporter he will adapt to that life style.