5th edition of IoT Middle East 2020 conference will be held at Armani Dubai and will cover a range of topics including how to generate business out of Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML) and Intelligent automation as the adoption of IoT is expected to accelerate over the coming years

An impressive line-up of speakers will be addressing how to manoeuvre the IoT landscape for higher profits at the 5th Internet of Things 2020, held at Armani Hotel Dubai on the 24th of February, 2020.

The cross-industry C-level conference aimed at decision-makers in both the private and public sector focuses on the business aspects of digital transformation. The event brings together forward-thinking experts sharing insights on business, technology and organizational transformation to leverage new business and new eco-systems.

Attendees have the rare opportunity of networking with experts, discussing the optimization of company revenue, reducing costs, changing business models, opening up new services and markets for key stakeholders and disruptive new entrants.

According to Johan Ehrstrom, CEO of 5th IoT Middle East 2020, “Collaboration is the new competition and eco-systems will replace traditional industry boundaries. New tech like AI and ML needs the data of IoT to deliver accurate analyses and output. IoT adoption is hence expected to grow by two-digit numbers and reach $18 billion in MEA related IoT investments by 2023, as both governmental and private sector companies ramp up their digital transformation capabilities.”

“The 5th Internet of Things 2020 is a game-changing platform, attracting over 400 attendees yearly, addressing the business relevance of technology across multiple verticals. IoT Middle East 2020 is for all who are less interested in the tech-aspects, but eager to future proof strategies, grow the bottom-line impacts and set the direction for the new decade.”

Over 30+ international and regional speakers, including executives from PwC, Evoteq, du, McKinsey, Karlsruhe Institute of Technology, London Business School, Cigna, Iqvia, Haltian and PTC will take the stage and highlight novel utilization of technologies designed to shape the foundation of the future success stories.

Participants can register on www.iot-dxb.com. Registration is now open for USD 745 for individual tickets, ask for group and management team tickets discounts.

The post IoT Middle East 2020 conference deep-dives into the next wave of innovations appeared first on Artificial Intelligence.

In the mass production revolution of the 20th century, machines sat side by side with humans replacing toil and sweat. Today, machines (let’s call them bots), are now doing the same, only for our brains instead of brawn.

While clearly helping both businesses and employees break the shackles of mundane, time consuming and inefficient tasks, the boom in bots isn’t creating the wholesale changes some futurologists and doom-mongers would have you believe.

In fact, we’re talking about replacing tiny corners of human intelligence with very specific, task-focused bots. Some follow rules and replace fingers (RPA bots), others chat (as long as the conversation is pretty dry and focused), while some use experience captured in thousands of rows of training data to make decisions.

What can be automated, and when?

The upshot being that many companies are deploying new intelligent automation technology, beginning with robotic process automation (RPA). But this is far from a ‘cure all’ solution. Quite the opposite in fact because it brings a series of separate challenges relating to what to automate, and when, which are actually the key question businesses need to be addressing.

In some organisations, this can be a simple question to answer because there is one clear task that takes a lot of time and fits within the capabilities of the chosen RPA tool. However, in most others it is more complicated and requires much more consideration. When assessing what to automate and when, businesses need to answer five key questions:

1. What’s it worth? – This is about understanding all of the activities and processes that can potentially be automated in an organisation and, more pertinently, what is the value that can be extracted through that automation. At its simplest level, this is knowing each activity cost.

2. Is it possible? – Namely, is the automation technology available right now to automate certain activities within the organisation? Of course, the answer to the question changes month on month, year on year as new technology is delivered into the market.

3. Can we do it? – Very often this comes down to complexity. There is clear evidence that automating large numbers of simple things delivers more value to an organisation than doing the same for a small number of complex processes. In short, if a business can deliver £1M of value by automating four complicated processes or 12 simple processes, most organisations will hit the £1M faster by choosing the 12 simple processes.

4. Is it sensible? – If a particular process is currently undergoing significant change – for example for regulatory reasons – then it isn’t sensible to start automating those activities when it is likely they will require reinvestment in two or three months’ time. Also, if there is variability within a specific process, for example, a task ranging from two to 20 minutes to completion, then it is likely there is a high degree of decision making in the process and without significant investigation, it is impossible to know if this variation is rules based or driven by experience. Either way, the whole decision process will need to be coded into or learned by your automation tool, which takes time and money.

5. Is it right? – It’s easy to deploy automating work that simply should not be done in the first place. Businesses know that automation resources are like hens’ teeth and getting the most out of them is essential. What is self-evident is that automating failure demand – i.e. automating work that is only being done because a part of the business failed elsewhere like logistics or customer service, is not smart use of automation investment. Neither is it a way to use these new and exciting technologies to deliver the best experience to customers.

Finding the answers

It is perfectly possible to pay a team of consultants to analyse the processes and create a detailed assessment. The only problem is that it’s a one-shot piece of work and it’s expensive. Businesses can also try and create a repeatable way of collating this data from existing systems, however it tends to be either non-existent, inaccurate or difficult to access in these systems.

Smart businesses are turning to robotic service orchestration (RSO) as an answer. It is a new technology specifically designed to address the challenges of automation at scale, and answer the five questions above – although to explain how it does that is a different article altogether.

To quote a business evergreen phrase, “change is the only constant”. What might be the highest priority to automate today, might not be tomorrow as business priorities, demand and technology move the goalposts. Yet, in spite of this, these key challenges will remain for any business looking to automate at scale.

The post 5 challenges of intelligent automation at scale appeared first on Artificial Intelligence.

As it relates to technology, the private aviation industry has been flagging lately. While some industries — health, retail, manufacturing, automotive — have adopted machine learning in recent years and used it to transform their businesses, our sector has fallen behind.

What the private aviation industry specifically lacks is machine learning technology to streamline workflows, business processes, customer procurement, and financial settlements. Midway through 2017, however, a corner is being turned, and aviation companies are increasingly starting to deploy consumer-facing technology to bolster customer service.

The private aviation industry has lagged behind many commercial airlines where technology is concerned. But delivering a service built upon automation and intuitive self-learning that fulfils every need of that highly demanding customer segment, the private flier, is a particular challenge.

Improving service via machine learning

To date, machine learning technology in aviation has mostly focused on the control of aircrafts or their internal systems. Most organizations are currently obsessed with the idea of automated piloting for self-flying planes. While that phenomenon is on the horizon, there are more immediate ways for us to use machine learning to enhance customer experience.

Whether you’re working in private or commercial aviation, there’s never been a more exciting time to be in the sector. We’re seeing airlines like Etihad Airways use machine learning to provide more personalized services to its passengers. Other airlines, such as EasyJet and Emirates, are using these advances to simplify the ticketing process and enhance internal operations.

Over time, the goal for the industry will be to leverage automation to personalize private charter for global travelers, as well as make the booking process more transparent, timely, and accessible. It’s all about smoothing and enhancing the flying experience for customers.

Additionally, private jet providers and airlines must leverage machine learning to identify how customers engage with the brand, detect their purchasing patterns, and segment them accordingly. By learning whether consumers prefer to make requests via a mobile app or the web, what time of the day they prefer to fly, and the amount they are willing to pay for flights, those companies will better understand and cater to consumer behavior.

It’s also imperative to know whether consumers are more influenced by prices, the various amenities that come with different jet options, or both. That kind of important information will allow private jet providers and airlines to adjust their offerings to best build genuine, long-term engagement.

Machine learning will ultimately help private and commercial aviation companies service their customers more effectively than ever. By helping customers make smarter, better-informed travel decisions, they will give customers greater control and instill loyalty. To reach that objective, however, they must operate on a healthy combination of intelligent automation and skillful human resources.

Increasing efficiency through AI

This is a ground-breaking period for society, not just aviation. Gartner estimates that six billion “connected things” will require AI support by 2018. Inevitably, the rise of automation will mean some human workers in our industry losing their jobs. But in the long run, I don’t think that is tremendous cause for concern.

The reality is that any tasks that take less 10 seconds to perform should be automated. Why? By automating more basic undertakings, aviation businesses can enable their employees to focus their efforts on improving the quality of the human interactions between their brand, the marketplace, and consumers. It’s about striking the perfect balance of hi-tech and high touch.

Although some employees will be phased out in favor of automation, it’s a net positive for any aviation company to perform more work for customers — and maintain a high level of performance — with a lower headcount.

Automation will also catalyze innovative new services that make private jets more available to the wider public, not just the elite. Within the next decade, I anticipate that the private aviation industry will have a mobile application that simplifies how customers can share jet charters with one another, like a carpool service for flights — assuming we can overcome regulatory hurdles. If it comes to fruition, this could stimulate new business and create human employment in other valuable ways.

Sharing a private aircraft will eventually prove as effortless as creating a WhatsApp group or sending images via text. As ecommerce platforms evolve, the concept of fluidly promoting and selling seats on booked charters will solidify. By leveraging the capabilities of social media networks, jet providers will not only help primary charterers defray their costs (attractive for business flights) but ensure that private air travel becomes ever more efficient and flexible. This kind of connected movement is the future of transportation for our busy world.

To gain new customers and keep them, private and commercial aviation companies must leverage machine-learning algorithms to truly understand their consumers’ preferences and deliver personalized, forward-thinking offerings accordingly. Otherwise, they’ll never shed the late bloomer label.

The post Machine learning could make flying less terrible appeared first on Artificial Intelligence.