AI and Robotics, Getting Smarter Rather than Tougher

The new wave of cobotics—robots that can safely work alongside humans—offers tremendous possibilities for industry. And with artificial intelligence (AI), smart robotics is changing the game. Thanks to new cognitive capabilities, robots can perform more than just repetitive tasks. DirectIndustry e-magazine interviewed Raun Kilgo, Director of the Robotic Process Automation division at technology research firm ISG.

DirectIndustry e-magazine: How would you define AI in robotics?

Raun Kilgo: Your workforce is human intelligence, in contrast to AI. When you give workers a framework or guidelines, they’ll spot patterns and understand how to complete tasks. Artificial intelligence is the ability of a far simpler machine than the human brain to exhibit the same level of pattern recognition, propose solutions and direct outcomes without human intervention.

DirectIndustry e-magazine: What kinds of robots can use AI?

Raun Kilgo: Industrial and mechanical robots, definitely! A robot making a car must be able to identify an inferior piece of steel intended for the hood. This requires inspection and heuristic activity to ensure that what it’s being asked to do is possible given the input. Information bots have to do the same thing when trying to understand the variability of human speech patterns and what people are asking for.

The real question is how to make sure humans are not supplanted by robots!

DirectIndustry e-magazine: How do you make sure robots can operate safely in factories alongside humans?

Raun Kilgo: The real question is how to make sure humans are not supplanted by robots! If mechanical robots become powerful enough to manufacture things independently, we must discuss the rules governing bot operations. Keep in mind that information bots can do as much good and as much harm as assembly line bots. If a bot sees something suspicious concerning my credit card while I am traveling abroad and blocks it without warning, I could be stranded. That’s why it’s crucial to establish additional controls so that AI systems don’t rely on just one or two data sets to make decisions. Maybe you need a human at the end of the line to make the decision, especially if the consequences could be serious for an individual. We need to keep a human involved in the decision making process.

DirectIndustry e-magazine: Who are the major players in AI and why are they getting involved?

Microsoft Tay
Raun Kilgo: Microsoft, Google and Amazon. But also robotic process automation people. Many heavy manufacturers are investing in AI. Everyone needs to enhance their decision making process without adding significant workforce overhead. They all want to make better decisions for their company and their customers, or optimize manufacturing efficiency.

DirectIndustry e-magazine: What do you think about Microsoft’s AI chatbot, Tay, which turned into an extremist after a couple of days on the web?

Raun Kilgo: Microsoft thought the bot would find good food. But people were malicious. Many feel threatened by bots and react negatively. They will do what they can to destabilize them. When we implement AI, the worst thing we can do is leave it alone. The best thing is to manage it, control it, understand it.

DirectIndustry e-magazine: Does that mean we need to redefine Asimov’s Laws of Robotics?

Raun Kilgo: Those laws are really simplistic and outdated because there’s no distinction between hardware and software. We definitely need new rules. This is what’s happening with self-driving cars. New concepts of governance need to be put in place to tell bots when to shut down rather than risk damage. AI is going to be a tremendous benefit for us. We’re going to have fewer workers, but they’ll be highly skilled. We need to maintain human involvement. It’s a slow invasion, but we’re already tied to it.

Source: emag.directindustry.com-AI and Robotics, Getting Smarter Rather than Tougher

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Are Chief Artificial Intelligence Officers Really Necessary?

As artificial intelligence (AI) begins to become more popular throughout businesses and industries across the world, we are now seeing robots in places we would have never imagined including supermarkets, hotels, and call centers. And, with the introduction of all the AI comes the need to oversee it and ensure it works in the business’ favor of course. But is the role of a chief artificial intelligence officer really necessary?

Companies such as Amazon, Facebook, and Google are making AI a central part of their core intellectual property as they recognize the solutions it brings to the sales, manufacturing, logistics and business intelligence sectors. They’re employing the use of AI to try and improve productivity, implement automation, and provide predictive analysis. Using AI within their business models, these companies have a competitive advantage in helping to solve real business problems.

Many people are arguing that if you’re going to have an AI system in place, you should hire Chief AI Officers to drive the AI strategy. But, there are also those believe that’s an unnecessary move to make. The main thing that needs to be done when implementing any new AI into the business model is first to understand the business’ problems and goals. Hiring a Chief AI Officer will not get you this. Instead, you will get someone freshly trained in a relatively new field looking to implement a range of AI technologies into your organization, with their main goal being to use AI rather than solve real problems.

So, instead of hiring a Chief AI Officer, one alternative is to deal with the problems. Give the AI to the people that are dealing with these problems day in day out. These will be the people best equipped to be able to implement effective solutions as are in the very heart of it. At the end of the day, there is no magical AI solution to solve every business issue. AI will help, but ultimately it is down to the people that run the business, and that know the business inside out that will make the real difference when implementing AI systems into the organization, not a Chief AI officer.

Source: trendintech.com-Are Chief Artificial Intelligence Officers Really Necessary?

Q&A. AI and Robotics, Getting Smarter Rather than Tougher

The new wave of cobotics—robots that can safely work alongside humans—offers tremendous possibilities for industry. And with artificial intelligence (AI), smart robotics is changing the game. Thanks to new cognitive capabilities, robots can perform more than just repetitive tasks. DirectIndustry e-magazine interviewed Raun Kilgo, Director of the Robotic Process Automation division at technology research firm ISG.

DirectIndustry e-magazine: How would you define AI in robotics?

Raun Kilgo: Your workforce is human intelligence, in contrast to AI. When you give workers a framework or guidelines, they’ll spot patterns and understand how to complete tasks. Artificial intelligence is the ability of a far simpler machine than the human brain to exhibit the same level of pattern recognition, propose solutions and direct outcomes without human intervention.

DirectIndustry e-magazine: What kinds of robots can use AI?

Raun Kilgo: Industrial and mechanical robots, definitely! A robot making a car must be able to identify an inferior piece of steel intended for the hood. This requires inspection and heuristic activity to ensure that what it’s being asked to do is possible given the input. Information bots have to do the same thing when trying to understand the variability of human speech patterns and what people are asking for.

The real question is how to make sure humans are not supplanted by robots!

DirectIndustry e-magazine: How do you make sure robots can operate safely in factories alongside humans?

Raun Kilgo: The real question is how to make sure humans are not supplanted by robots! If mechanical robots become powerful enough to manufacture things independently, we must discuss the rules governing bot operations. Keep in mind that information bots can do as much good and as much harm as assembly line bots. If a bot sees something suspicious concerning my credit card while I am traveling abroad and blocks it without warning, I could be stranded. That’s why it’s crucial to establish additional controls so that AI systems don’t rely on just one or two data sets to make decisions. Maybe you need a human at the end of the line to make the decision, especially if the consequences could be serious for an individual. We need to keep a human involved in the decision making process.

DirectIndustry e-magazine: Who are the major players in AI and why are they getting involved?

Raun Kilgo: Microsoft, Google and Amazon. But also robotic process automation people. Many heavy manufacturers are investing in AI. Everyone needs to enhance their decision making process without adding significant workforce overhead. They all want to make better decisions for their company and their customers, or optimize manufacturing efficiency.

DirectIndustry e-magazine: What do you think about Microsoft’s AI chatbot, Tay, which turned into an extremist after a couple of days on the web?

Raun Kilgo: Microsoft thought the bot would find good food. But people were malicious. Many feel threatened by bots and react negatively. They will do what they can to destabilize them. When we implement AI, the worst thing we can do is leave it alone. The best thing is to manage it, control it, understand it.

DirectIndustry e-magazine: Does that mean we need to redefine Asimov’s Laws of Robotics?

Raun Kilgo: Those laws are really simplistic and outdated because there’s no distinction between hardware and software. We definitely need new rules. This is what’s happening with self-driving cars. New concepts of governance need to be put in place to tell bots when to shut down rather than risk damage. AI is going to be a tremendous benefit for us. We’re going to have fewer workers, but they’ll be highly skilled. We need to maintain human involvement. It’s a slow invasion, but we’re already tied to it.

Source: emag.directindustry.com-Q&A. AI and Robotics, Getting Smarter Rather than Tougher

Blue Prism Accelerates Access to AI and Cognitive Technologies with Operating System for the Digital Workforce

New Program Enables Technology Partners to Build out Best of Breed Capabilities on Industry Leading RPA Platform

Blue Prism, provider of the world’s most successful digital workforce, today announced a new Technology Alliance Program backed by industry heavyweights including Appian, Captricity, Celaton, Expert System, IBM and Minit. These partners will leverage Blue Prism’s Robotic Process Automation (RPA) platform to help enterprises build out best-of-breed solutions incorporating cutting edge cloud and artificial intelligence (AI) capabilities. The partners also help to underline Blue Prism’s position as the de facto standard for RPA, particularly in heavily regulated industries such as financial services, insurance, healthcare, telecom and retail.

“Our customers are seeking best-of-breed software and service providers for AI, cognitive; OCR and ICR, workflow and mobile platforms. Having described and encapsulated their processes on our platform, they have the opportunity to deploy an ecosystem of technologies that work in concert, using Blue Prism robots to provide transaction execution and process automation services, much like an operating system,” explained Blue Prism Founder and Chief Technology Officer Dave Moss. “Our software robots are becoming the foundation for more than automation: they are becoming the cornerstone for building out the next generation of enterprise-grade applications.”

Blue Prism’s Operating System for the Digital Workforce not only encapsulates and automates manual processing but also enables organizations to leverage, integrate and more efficiently utilize IT resources, platforms and technologies. The software is designed to deliver a complete automation platform that can meet the highest requirement levels for audit, security and compliance while taking advantage of cloud and AI capabilities. This gives partners and users alike an automation platform that accelerates access to emerging technologies while delivering on all the key tenants of enterprise-class software.

By leveraging Blue Prism’s technology ecosystem, customers benefit from a cohesive, best-in-class automation platform to form the operating system for the digital enterprise and deliver enablement, execution and insight on a robust and extensible RPA platform. The ecosystem supports examples such as using text analytics to provide insight into a stream of unstructured data from an email source, or directly querying a machine learning model from a Blue Prism process, to provide predictive responses.

Alastair Bathgate, Blue Prism’s CEO, stated, “We have been working with the foremost transformation advisors and partners to deliver digital transformation programs to many of the world’s largest corporations in the most demanding operational environments. For example, more than half of the Global Fortune 500 companies in Banking and Insurance have embarked upon digital transformation journeys with Blue Prism as their core Enterprise RPA platform.”

Phil Fersht, CEO of HfS, the leading RPA and digital labor analysts firm, noted, “We see an enormous move towards fully digital enterprises, and customers are looking for best-of-breed solutions that can be integrated into one digital automation platform. Blue Prism and its partners are now offering this capability, and it will be fascinating to see just how the digital workforce will accelerate the digital enterprise.”

Partner Quotes

“With IBM’s deep industry expertise, a full-range of consult through operate solutions, and most importantly, by combining our market leading cognitive capabilities with traditional RPA, we are leading with cognitive process automation, the next generation of RPA to accelerate our clients’ digital transformations,” said Jesus Mantas, General Manager of Cognitive Process Transformation, IBM Global Business Services. “Cognitive process automation is improving the efficiency of IBM clients’ processes beyond automation. For example, in procurement, human resources and finance, we are seeing an increase in productivity of 40 to 60 percent in some tasks by driving fundamental changes in the way work gets done.”

“Appian’s platform powers digital transformation for many of the world’s leading brands. We’ve found integrating with Blue Prism a simple and effective way to extend the power of Appian,” said Michael Beckley, Appian’s CTO. “Many organizations today are held back in their transformation efforts because they have a portfolio of legacy applications. Appian and Blue Prism can help these organizations transform more rapidly while avoiding or minimizing legacy integration projects. This partnership builds on the history of integrated Appian and Blue Prism solutions in production at our clients today.”

“As the inventor and leader of RPA, Blue Prism knows that RPA is becoming pervasive across all enterprise architectures and platforms,” said Christopher Lynch, VP of Sales at Captricity. “Captricity’s partnership with Blue Prism enables our largest customers to automate their end-to-end workflows, without the need for complex integrations or large-scale IT projects. We are excited to work with Blue Prism as part of our ongoing strategy to build a valuable partner ecosystem for some of the biggest life insurers in the world.”

“Celaton’s machine learning capabilities combined with Blue Prism RPA enables organizations to achieve efficiencies that were previously out of reach,” said Andrew Anderson, CEO of Celaton. “All inbound information streams can be brought into automations regardless media channel, format or unstructured nature of the data.”

“Our joint customers are the most effective proof of the complementarity between Expert System’s Cognitive Technologies and Blue Prism’s automation platform,” said Marco Varone, Founder, CTO and President of Expert System. “Together we strive to make full automation a reality while maximizing the business value of RPA. We are excited to establish a solid partnership with Blue Prism with the intention of making AI a strategic factor for success in support of a wide range of organizations worldwide.”

“Our clients can now take RPA to the next level using Blue Prism. From planning and initial analysis, to identification of areas where RPA can help the most, to continuous testing and improvement in real-life scenarios, this program will bring powerful and quantifiable technology advantages to our customers,” said Jaroslav Zubak, CTO for Minit.io. “Minit is driving the digital transformation process by enabling customers to turn their data into actionable results backed by 100 percent accurate data. We’re proud to be a part of this automation transformation initiative.”

Source: blueprism.com-Blue Prism Accelerates Access to AI and Cognitive Technologies with Operating System for the Digital Workforce

21 Bot Experts Share Their 2017 Predictions

2016 was a huge year for bots, with major platforms like Facebook launching bots for Messenger and Amazon and Google heavily pushing their digital assistants. Looking forward to 2017, we asked 21 bot experts, entrepreneurs, and executives to share their predictions for how bots will continue to evolve in the coming year.

1. Andy Mauro, CEO, Automat

In 2017 brands will realize that Conversational Marketing is a better way to learn about and build relationships with their customer than today’s digital marketing which monitors their customers with cookies, pixels, search and social data. We’ll also see powerful case study data showing that opt-in and conversion rates and the quality of profile information that can be obtained conversationally far outweighs the benefits of email marketing, marketing automation and apps

2. Tania McCormack, Director of Product Management, Flowdock

Bots will be even more helpful, more intuitive, and most of all, more human. In Flowdock, we aim to have our users interact with bots like we do the people around us to get the information and updates we need. Best of all, bots will continue to keep work fun and to make us laugh.

3. David Mendlewicz, Co-Founder, Butterfly

We’re going to see more and more instances of bots helping us develop and grow as humans. To date, bots are primarily seen as a novel utility–a way to get things done more quickly or grasp information more immediately. Moving forward, the machine genius of bots will help understand our learning gaps and fill them in with relevant, personalized information that’s rooted in real data. In other words, bots will be a boon for education.

4. Ben Parr, CMO and Co-founder, Octane AI

There will be an explosion of unique content and experiences from bots as the barrier to creating and managing them drops. This will lead to some breakout bots. Some people will be famous primarily for their bots.

5. Justin Vandehey, Founder, Growbot

In 2017, I think we’re going to see bots grow up a bit, both in terms of standards for how they should be built and how they should be used. There’s a finite set of core workflows and jobs that can be improved. Bot builders who identify those workflows and fit in without requiring a ton of behavior change…those, are the money bots.

6. Jordi Torras, Founder & CEO of Inbenta, Inbenta

Chatbots will get increasingly smart, thanks to the adoption of sophisticated AI algorithms and machine learning. But also they will specialize more in specific tasks, like online purchases, customer support or online advice. First attempts of chatbot interoperability will start to appear, with generalist chatbot, like Siri or Alexa, connecting to specialized enterprise chatbots to accomplish specific tasks. Functions traditionally performed by search engines will be increasingly performed by chatbots.

7. Dan Reich, CEO, Co-Founder, Troops

The word “bots” will slowly go away as people realize that the value is less about talking to a computer or bot, and more about having intelligent workflow within a conversational platform.

8. Dmitriy Kachin, Head of Partnerships, Chatfuel

1) AI Technology – once the Machine Learning aspect of the current AI engines moves on to the next level, and the NLP functionality becomes more sophisticated, we should see some really interesting breakthroughs in terms of chatbot experiences that will appear as a result of that. 2) E-Commerce – when the ability to monetize your bot becomes more robust with solutions integrating CRM systems, warehouse management systems, order tracking, etc – there will be a lot more motivation to realize your offering in a chatbot form. The resulting increase in various e-commerce use cases and the corresponding user traffic should be interesting to watch. 3) As a result of 1 and 2, overall wider adoption of bots.

9. Rob May, CEO and Co-founder, Talla

This year, we’ll finally see large enterprises adopting chat. In our own lead flow at Talla we’ve seen that Fortune 1000s are exploring platforms and what they can do with them. This is how people want to work—and they’re seeing the vision too. We’re at the tipping point where they’re starting to cross over. As a result, we’ll see the integration ecosystem continue to mature into more robust solutions.

10. Lauren Kunze, CEO, Pandorabots, Inc.

Right now the industry needs data driven success stories as an antidote to hype, and this year certain bot applications will increasingly yield real business results. This will help brands filter the noise and differentiate upstarts from industry leaders. Beyond 2017, I predict bots will be the primary interface for casual interactions between people and brands, and people and connected things.

11. Amir Shevat, Head of Developer Relations, Slack

We will see conversational interfaces facilitating productive business workflows. We will see bots augment our life experiences in text and voice in consumer use cases.

12. Mikhail Naumov, Co-founder, CSO, DigitalGenius

In 2017 brands will understand when to use scripted chatbots and when to use machine learning algorithms. Customer Service functions in particular will be significantly transformed with latest advances in deep learning and artificial intelligence. Human and machine intelligence will be combined in a seamless way, to make great experiences for customers.

13. Zor Gorelov, CEO & Co-Founder, Kasisto

We expect the bot landscape to expand in 3 key areas: monetization, security and overall growth in capabilities. A marketplace on popular platforms will enable discovery and in-app transactions. This will drive a higher standard for security, especially in privacy-centric industries like banking, insurance or healthcare. The more companies and players in the space, the faster the bots will improve and the more useful they will become.

14. Marlene Jia, Chief Revenue Officer, TOPBOTS

Bots will be built with specific use cases and objectives in mind driving actual adoption of the consumer.. 2016 was a year of experimentation for both the brands and users, and there were a lot of learnings that emerged. In 2017, you’ll see brands and bot creators doing a better job identifying the use case for the bot and the narrow goals of what the bot should be able to do. We can’t guarantee AI will be at the stage it needs to be to make bots intelligent enough, but what we can do is have a clear idea of what the bot should do and design it based on that objective.

15. Matthew Hartman, Partner, Betaworks

We will start to see a set of bots that are growing, solving the discovery problem in unique ways. We’ll also start to see messaging services experiment with monetization that feels native and unique.

16. Oren Jacob, CEO, PullString

We will see Alexa voice experiences grow substantially in usage, reach, and complexity. A lot of amazing things are being built for the Alexa platform.

17. Jeff Pulver, Founder, MoNage

The way “we” experience the Internet is changing, and that the result of the shift in how communication evolves will be highly disruptive. Communications will be better, easier and more relevant for us Internet users as a result of AI. Summing up the change, the interface between humans and computers is rapidly changing from an “operational” interface (Websites, apps) to a “conversational” interface (ChatBots, voice interfaces). This is revolutionary, given that the “operational” interface has been the standard way to interact with computers since the earliest computers came on the market.

18. Dennis Yang, CoFounder & CPO, Dashbot

We are already seeing continued strong growth in the bot space across all platforms for the first part of 2017. I predict we will see a number of bots hit one million DAU by the end of 2017. Furthermore, we will begin to see more bots that fully embrace the capabilities of conversational UIs, differentiating themselves from the web & mobile experiences to which we are currently accustomed.

19. Tom Hadfield, CEO, Message.io

2017 will be the year of the conversational workplace. With the launch of Slack Enterprise Grid, Microsoft Teams, Google Hangouts Chat and Workplace by Facebook all in the first four months of the year, the enterprise messaging space is proving to be where bots are finding mainstream adoption. 2017 will be the year that conversational interfaces begin to transform the $620 billion enterprise software industry, just as the graphical user interface did in the 80’s, the web did in the 90’s, and mobile apps did more recently.

20. Sandeep Chivukula, Co Founder, Botmetrics

More push; Less pull. Today bots react to customers. The best bots of 2017 will predict what’s improtant to customers and help them take action.

21. Rachel Law, CEO/founder, Kip

The line between software bots and robots/drones will blur as physical bots integrate into platforms. Soon you’ll be able to control roombas and drones through Messenger!

 

Source: topbots.com-21 Bot Experts Share Their 2017 Predictions

Robotic process automation – a new frontier in customer service?

Customer service has always been a key business differentiator. However, recent technological progress, greater consumer choice and eroding loyalty means the empowered customer will no longer stand for sub-standard experiences. As a result, the past few years have seen a renewed focus on the consumer.

This is being reflected in internal business structures across sectors. Where once the customer would be the sole responsibility of the marketing department, they have now become a company-wide responsibility. From the c-suite to IT, brands are placing the customer at the heart of every department and designing their processes and structure with customer fulfilment at the centre of their thinking.

Digital transformation

The digital revolution has driven further advances in customer experience, allowing consumers to interact with their favourite brands whenever and however they want. Digital tools such as webchat, apps and social media are the norm – and in the race to provide the best customer service, forward-thinking brands are now experimenting with the latest technology to create novel, value-added solutions for their clients.

This is in part driven by journey mapping. At Firstsource, we use Interaction Analytics (FCI) to map the customer experience across all touchpoints, highlighting the ‘make or break’ moments – those reasons for customers to exit any given process – in the overall journey. From there, we work with brands to improve the pain points and policies and help make them more customer friendly.

Our experience tells us that customer experience is all about convenience, so it’s important businesses stay on top of what convenience looks like. This depends on integrating new channels to help businesses interact on customers’ own terms, which is why we’re currently looking at how we can use popular messaging platforms such as WhatsApp to deliver tailored communications in real-time, for example.

While traditional contact channels such as voice and email will always be important, new technologies helps connect brands with digitally-savvy customers. As an added bonus, businesses also get the kudos that come with appearing as an innovative and customer-focused brand.

The automation opportunity

Robotic Process Automation (RPA) is one of the newest frontiers in customer service. At its core, RPA is the application of a computer software or “robot” to process transactions, manipulate data or trigger responses, depending on the scope of the request. This technology has the potential to unlock value across a wide range of different industries and business functions. In particular, regulated industries with high volume and transactional business processes stand to gain significant benefits from the application of RPA.

Done well, it can deliver more cost efficient, streamlined and compliant processes. At the same time, automation allows employees to focus on higher value activity that will drive customer experience. It’s a win win for businesses who get it right.

However, while appetite for robo-advice among consumers is growing, it’s clear that automation requires careful due diligence to understand the opportunities, risks and requirements for delivery.

And consumers understandably still have their doubts when it comes to automated advice. A recent study conducted by Firstsource showed that 44 per cent of consumers see the availability of a bank branch as their number one deciding factor when choosing their banking provider – telling a cautionary tale for businesses undergoing digital transformation.

RPA transformation

Needless to say, integrating RPA is a significant undertaking. While the specifics will depend on the business, the sector they operate in, and the extent to which they are aiming to automate their processes, there are three critical ingredients for a successful RPA transformation.

The first – and perhaps most important – is that RPA must be a strategic fit for the company. RPA needs to be understood not as a process but as a strategic capability that increases business value. This re-engineering will be key to increasing the impact of automation and maximising ROI, and must be given due diligence – so it’s vital businesses understand which processes will deliver the biggest business benefit when automated, and construct a careful roadmap accordingly.

Next, there also needs to be buy in for transformation and automation from the C-suite for RPA to be a success. Cultural adoption may often require education and careful articulation of the business benefits of the solution, and lack of internal support at a senior level can be one of the major stumbling blocks to RPA implementation.

Unsurprisingly, successful automation also relies on IT engagement. Legacy IT systems and resistance from existing IT departments can often be a barrier to transformation and automation. Bringing the IT function on board at the beginning of the automation journey will help to set a clear roadmap for transformation and identify any potential roadblocks that lie ahead.

RPA in practice

When thinking about the ways businesses can use RPA, most peoples’ thoughts turn to chatbots. Microsoft, Uber and Twitter are just a few brands who have recently launched bots for customer service – although some with more success than others.

While they have the potential to go very wrong, chabots can be useful to solve straightforward transactions and simple queries. They can also help shepherd customers on a relatively linear journey, such as answering delivery questions on an order.

But RPA can be used for more than just straightforward customer engagement. It also has the potential to transform back office processes, freeing-up employees from repetitive tasks to focus on more complex and value-added work. And it can also be used to transform more complex processes, such as commercial finance operations. This is particularly valuable in the financial services industry, where many businesses rely on the efficient and cost-effective running of their commercial finance division to keep them in business.

But often, the smooth running of these operations are hampered by inefficient, expensive and cumbersome legacy technologies. And while many businesses recognise that this is holding them back, they lack the skills, resource and expertise to overhaul the outdated systems and processes. Outsourcing commercial finance operations can be an effective way to transform a business through automation with lower risk and resource.

By simplifying and automating processes and redesigning operating models, many large-scale financial organisations should be able to increase productivity in their commercial finance operations by between 30-50- per cent, while reducing cost to serve by 25 per cent.

Whether it’s customer-facing or in the back-office, brands have a lot to gain by integrating RPA in their operations. What’s clear is that automation is here to stay and evolve – and businesses must determine how it can play a key role in delivering the best customer experience possible.

Source: itproportal.com-Robotic process automation – a new frontier in customer service?

Automation across financial services: hype or reality?

Whether the displacement of human labour by automation is, as is often depicted, another nail in the manual coffin seems a moot assertion. But what cannot be denied is its increasing role across the financial services (FS) sector, with some players even seeing automated environments as a panacea.

Universal remedy or not, what does seem clear is that the FS sector is ripe for automation. Supporting this assertion is a 2017 report by Infosys – ‘Amplifying Human Potential: Towards Purposeful Artificial Intelligence’ – which found that FS companies across the globe (based on a poll of 1600 senior business decision makers at some of the world’s largest organisations) are looking to automation, and its subset, artificial intelligence (AI), to boost revenues and streamline structures.

“Financial institutions (FIs) are looking at automation across a fairly wide spectrum of activities,” says Tom Kimner, head of global risk marketing and operations at SAS. “One recent area of interest has been an investigation of current processes around governance and compliance. With many of these processes stabilising to some degree, FIs are looking at improving and streamlining them with some form of automation to not only reduce costs but to make them more robust and repeatable.”

Clearly, the use of automation and AI is expanding and evolving across many industries, with the FS sector a particularly active participant. Indeed, according to Infosys, companies in this space have each invested, on average, $14.5m in AI technologies to date, compared to an average of $6.7m in other industries.

The Infosys survey further reveals that: (i) 76 percent of senior decision-makers believe AI is fundamental to the success of their company’s strategy; (ii) by 2020, those currently or planning to use AI technology anticipate a 39 percent boost to their company’s revenue, on average; and (iii) eight in 10 companies that have replaced, or plan to replace, roles with technology will retrain or redeploy those who are displaced.

In its 2016 analysis of the automation debate – ‘How can RPA and other digital labour help financial institutions’ – PwC states that technology is now allowing FIs to automate many computer-based operational tasks like searching, matching, comparing, filing and more, which frees up staff to do much higher value work. Also highlighted are some of the repeatable and logic-driven activities which are deemed ideal for automation, such as: trade mismatches; management reports; regulatory information such as CCAR stress tests; client reporting; asset servicing; account opening processes, such as anti-money laundering and know your customer; and reconciliation and data remediation initiatives.

Many commentators expect the shedding of costly and cumbersome legacy IT architecture to continue apace. The stage is set for FS automation and AI to move from what was, only a few years ago, relatively vague concepts to bona fide, strategic business imperatives.

The shape of things to come

Automation can of course be found in some shape or form in virtually every industry. Its creation has greatly improved efficiency and substantially increased quality thresholds. Add to this the ongoing development of AI technologies – with numerous applications for insight, increased productivity and expanded possibilities – and the benefits of automation are abundantly clear, with the FS sector an obvious beneficiary.

“Intelligent automation has truly landed in FS, with the aim of reducing costs, simplifying processes and improving performance,” says Christopher O’Driscoll, a financial services expert at PA Consulting. “Specific trends and developments in robotic process automation, cognitive computing and Internet of Things (IoT) are being seen across banks, insurers and asset managers. These include machine learning being applied to credit risk processes, robo-advisers delivering investment advice and natural language processing being used for tasks such as speech recognition for account access. These trends will continue as automation is increasingly applied to an even wider variety of tasks.”

“The stage is set for FS automation and AI to move from what was, only a few years ago, relatively vague concepts to bona fide, strategic business imperatives.”

Further fleshing out the nature of such tasks is Capgemini’s 2016 report ‘Robotic Process Automation Solutions for Financial Services’, which proffers that optimising and improving efficiency means more than just upgrading systems or outsourcing processes – it means harnessing innovation. Repetitive tasks – which the Capgemini report estimates 40 percent of staff spend their time on – are essentially algorithms and therefore can be automated, with robotic process automation (RPA) innovation that combines user interface recognition technologies and workflow execution to follow predetermined computer pathways.

The effects of such innovation, from fighting fraud to improving the customer experience and even predicting the direction the market will head in, are already visible. “Contact tools such as the AI virtual agents introduced at a Japanese bank are a good example of how automation is already benefiting the FS landscape,” says Indivar Khosla, executive vice president and global head of FS business services at Capgemini. “They can respond and solve customer enquiries much faster, resulting in fewer calls to the bank’s main contact centre, therefore freeing up time for staff while improving the customer experience.”

Chatbot technology, which carries out complex calculations instantaneously, allowing customers to check their finances, evaluate their spending habits and monitor their credit score, is also having a big impact. The speed and efficiency of core business processes received a significant boost from the chatbot innovation.

Pros and cons

Like any endeavour poised to be a major disruptive influence on an industry’s status quo, automation in FS comes with a range of pros and cons. According to Mohit Joshi, president and head of banking, financial services & insurance at Infosys, by using automation, banks are distinguishing themselves by being technologically sophisticated and capable of meeting the financial and security needs of digitally savvy customers. “Some of the world’s largest credit card issuers, HSBC and JP Morgan Chase & Co. among them, utilise AI to analyse the buying patterns of their cardholders. Any anomalies are red-flagged and preventive measures taken before a cyber thief can do lasting damage. The 2016 Forter and PYMNTS.com ‘Global Fraud Index’ found that in the first quarter of the year, $4.79 of every $100 in online transactions was considered at risk. That is up from $2.90 year-over-year.”

Automation enables FS firms to create a measurable audit trail of activity, reduce human error, speed up transaction times, reduce costs and improve overall customer experience. But the reality, says Chris Gayner, marketing director at Genfour, is that many firms are still trying to deliver a significant return on investment (ROI) to justify further investment. “In our experience, those FS firms which are seeing ROI from automation, view automation as a journey and not a project – which typically means cross functional working, robust governance and employing the right skills to drive out maximum benefit,” he says.

Further obstacles to automation include budgetary concerns and a lack of technical capability, not to mention redundancies and the associated impact on company brand. Potential job losses is a sensitive issue in the automation debate, with no easy answers. That said, not all processes lend themselves to automation and, for those that do, the result may not be job losses but rather a form of job transfer to more important tasks like deeper, more thorough analytics. “It is important for organisations to have an understanding of what types of skills are needed now and in the future for any evolution toward automation they may consider,” suggests Mr Kimner. “Anticipating the right mix of skills is important as it will influence the types of training and the hiring that organisations may undertake.”

Dismantling architecture

An unavoidable issue when moving to automation is the need to dismantle existing IT architecture, protect underlying systems and, at the same time, keep costs under control. To help minimise costs during this process, IT architecture should be simplified and a service layer added, to allow a company to integrate its IT with other systems and intelligent automation technologies.

“Due to the size of FS organisations’ operations, changing their IT systems and ways of working can be a challenge,” says Mr Khosla. “However, investing in ways to improve the IT infrastructure and processes can help save on future costs which will only increase as systems and processes become increasingly outdated. These savings can then be passed on to other areas of the business, allowing other processes to be updated.”

One option favoured by Mr Gayner is for companies to have recourse to a considered automation roadmap – the first step toward minimising the cost of automation. Yet, given that automation tools can readily be found online and installed onto machines without involving IT, it makes sense for organisations to take a company-wide view of automation – who owns it, how it is managed and where it should be used. “FS sector firms should invest in a robust proof of concept to ensure the technology fits with their wider IT initiatives and complies with corporate policies, but also that the approach to automation is the right one. It is important that automation adds value, and is not just a replacement for bad processes,” explains Mr Gayner.

The transition from legacy systems to newer, more agile technologies and platforms is clearly a difficult and costly enterprise, with many companies mistakenly looking only at the technology costs of replacing various systems and not the total costs, which include, for example, change management, process improvement and resource training. “Organisations often start by acquiring some new technology and then trying to implement pieces of it through a patchwork of small projects that often seem like iterative, trial and error exercises,” attests Mr Kimner. “Thorough planning and an understanding of the impact and downstream effects of technology changes on people, as well as processes, must be part of a sound programme in order to keep overall costs in check.”

Embrace or resist?

With automation in FS continuing to evolve, the extent to which the sector will play ball with this evolution, whatever form it takes, is a matter of debate.“As traditional banks grapple with the challenges posed by FinTechs, legacy constraints and traditional operational models, AI is emerging as the saviour,” claims Mr Joshi. Indeed, according to the Infosys survey, 23 percent of 250 FS sector respondents confirmed that AI technologies have been fully deployed in their organisations. Moreover, 47 percent view AI as being fundamental to the success of their organisation’s strategy. “It is likely this trend will continue to accelerate and transform the financial services landscape. Furthermore, as AI is deployed more regularly and employees become increasingly familiar with it, adoption will be the common sense option,” adds Mr Joshi.

On the flipside, less focused firms could find themselves struggling to keep up with competitors taking advantage of the benefits that automated business processes can bring. “It is too early to say how far automation can go, but the next five to 10 years and beyond will certainly be exciting when it comes to the application of AI to business processes,” suggests Mr Khosla. “For under pressure FS firms, gross operating expense (GoE) reduction, return on equity (RoE) maximisation and transformation of the operating model are all key priorities. Moreover, as the technology behind automation develops, we will see it start to take on more complex tasks and create greater efficiency and potential within the workforce. Although challenges exist, AI has the capability to allow the industry to develop new highly personalised customer propositions and improve their experience.”

A tool for the future

In a landscape where competition, complex processes and regulatory demands are all challenging profits, automation is assisting the FS sector to reduce costs and reconfigure existing practices and business models. Furthermore, by making tasks more predictable and easier to control, automation is also improving performance and process quality, eliminating human error and improving efficiency.

“With the market becoming more competitive, FS companies are recognising the need to differentiate themselves,” says Mr O’Driscoll. “Automation can help with this, enabling FS providers to carry out processes faster so that new products and services can be brought to market quicker than the competition. From the robo-adviser to the automated back office, FS will continue to be a leader in the digital development, and an early adopter of RPA, cognitive technologies and AI. As the combination of high transaction volumes, level of customer service and regulation becomes ever more costly, automation will be increasingly applied.”

Going forward, it is of course difficult to predict the types, uses or limits of automation across the FS sector. However, it stands to reason that there will continue to be cases where the automation of repetitive processes, compliance activities and reporting, will be more cost effective and, in some cases, necessary. According to the 2017 ‘Robotic Process Automation: A Guide for Banks and Financial Institutions’, the global automation market is expected to see a compound annual growth rate of 75 percent, reaching $835m by 2020 – an adoption rate which strongly indicates that the sector will focus on investing for training and ownership of automation technologies.

“There will most likely be cases where automation is used to attract, convert and retain customers through various channels,” says Mr Kimner. “There may even be cases where automation is used in business decision management or perhaps portfolio optimisation. However, what is clear is that FIs need to look for ways to reduce costs and improve margins if they want to remain profitable and competitive – and automation is one of the tools that may well help them achieve this.”

 

Source: financierworldwide.com-Automation across financial services: hype or reality?

Intelligent adoption of artificial intelligence

Artificial intelligence (AI) is one of the most talked about technologies in recent times. It is capable of increasing enterprise revenue through identifying, analysing and, most importantly, acting on the insights from underlying data. The pertinent question is, “Should we wait for AI to evolve fully and then apply it or should we look at specific applications to solve business challenges?”

Range of AI—Human assistant to human replacement

The combination of parallel processing power, massive data sets, advanced algorithms and machine learning capabilities are spawning varied versions of AI systems.

Today, AI capabilities vary from specific/narrow to super, all-encompassing AI.

Narrow, or specific AI, is an intelligent assistant that can aid humans in making complex decisions and enhance their cognitive powers by processing vast amounts of data. It can conceptualize and correlate data, recognize the patterns and deliver intelligent output.

For instance, soft AI can be used to detect frauds in various sectors such as banks.

A large sample of fraudulent transactions is fed into the AI system, which is trained to look for signs that separate fake transactions from genuine ones.

Another example of soft AI is the voice assistant that can understand voice inputs, analyse data about the users from a variety of sources (social media, smartwatches, etc.) to better understand their behaviour and deliver results tailored to users’ preferences.

Super, or strong AI, aims to make decisions on its own without any external support.

These machines can think, learn, decide and converse like humans. Hence, they have the ability to replace humans altogether.

However, super AI systems are yet to achieve breakthrough improvisation to fully comprehend human mind-maps and replicate human intelligence.

How is AI different from RPA and cognitive?

Though enterprises are increasingly understanding the benefits of AI, there still exists misperception around similar technologies—AI, robotic process automation (RPA) and cognitive.

AI is described as the decision-taking capability based on simulation of human intelligence processes by machines. These machines “can act” as human.

On the other hand, cognitive computing helps humans in fully or partially delivering judgement-based processes and assists in their decision-making. These systems deal with unstructured inputs, and “can think” as humans.

The third type, referred to as RPA, can automate rule-based tasks and “can do” what humans can. Such systems lack self-learning capability and are effectively dumb: they just perform exactly as programmed.

AI-use cases in business

As customers are becoming increasingly demanding, AI offers assistance on key requirements of evolving business:

• People-centric: The AI systems enable the enterprises to shift to a people-centric approach from being process-centric. The decisions are made based on unstructured real-time data rather than pre-defined processes. For instance, ride-sharing companies predict fleet demand based on factors such as weather forecasts, time of the day and historical customer behaviour.

• Ease of use: AI enhances customer experience with offered convenience and assistance. For example, enterprises are using “customer digital assistants” that can recognize customers by face and voice to have relevant conversations, and provide tailored choices to help them make purchasing decisions.

• Self-adaptive: AI has the capability to self-evolve, make connections between data, improve on past decisions and get smarter. For instance, machine learning-based intelligence enables an enterprise to improve sales performance by accurately predicting cross-selling and up-selling opportunities.

AI implementation strategy for enterprises

AI has the potential to disrupt the core of business processes. However, blind adoption of technology and hype-based purchase may not lead to the desired results. Enterprises can ride the wave of success with efficacious adoption of AI technology:

• Getting familiar with the concept: Rather than adopt the technology in haste, enterprises should first educate themselves on the basic concepts and capabilities of AI. The better a company understands what narrow/soft AI does, the more likely is its successful adoption.

• Identifying the problem to which AI is a solution: Enterprises should identify specific use cases in which AI could solve business problems and help them achieve specific project goals. They should further narrow down the possible AI implementations by assessing potential business and financial values.

• Bridging the talent gap: AI requires talent pool with a strong understanding of advanced programming, domain knowledge and business context. Enterprises should bring these skills together instead of waiting for one person to bring all the dimensions.

The importance of AI is well understood. However, its implementation remains limited.

It is imperative for firms to start applying AI for solving narrow-scope problems before expecting it to disrupt the core of the business.

AI can be employed for everything from managing targeted advertisements to optimizing logistics to tracking assets to understanding the customers’ social behaviour. The trick is to get started on the right note.

Source: livemint-Intelligent adoption of artificial intelligence

The robots are coming: better get used to it

Every society needs an enemy: something which threatens the fabric of the nation. Whether it’s the barbarians at the gates of Rome, Reds under the bed, or the job-destroying stocking frames attacked by the Luddites, every age has its own perceived existential threat. Ours is robots.

This world will not just survive the rise of the robots, but benefit from them greatly. It’s true that they will disrupt the workforce, but the apocalyptic forecasts of mass unemployment are simply hyperbole, more fitted to a Brothers Grimm tale than a rational discourse of the near future.

What society needs are facts, not scaremongering. However, facts about the future (excluding death and taxes), especially with the pace of change and the uncertainty in the world are difficult to come by.

So let’s start with Forrester’s prediction that by 2019, a quarter of all job tasks will be offloaded to software or robots. It seems alarming and is certainly headline grabbing, until you read further and find, in the same report, that these technologies will create a further 14 million jobs in the same period.

No-one denies that a world powered by automation and AI will look very different from today, and no doubt some existing jobs will go the way of ostlers, farriers and blacksmiths. At the same time, technology will create entirely new careers, many of which people can only guess at today.

People should be accepting of this inevitable rise of the machine, because, for all the capabilities of AI, machine learning, RPA and robots, no technology comes close to the ingenuity of even the most average human mind.

The problem is not that robots will steal our jobs in the future: it is that humans have been wasting their faculties on tedious tasks that are much better performed by artificial intelligence or software, such as rekeying data or answering routine queries.

It will also help with the UK ‘productivity gap’, that the country has been suffering from for several years. The UK has been at the forefront of offshoring, lots of that efficiency gained from labour arbitrage can instead be delivered by robots and managed locally; driving more flexibility, control and efficiencies.

Far from being a jobs thief, new technology will augment the workforce, freeing them from repetitive, mundane tasks and using their higher abilities on more meaningful activity.

Take chatbots and AI assistants. Already these are replacing the time-consuming task of scheduling meetings, creating schedules – even taking notes in meetings. This means that the “cognitive load” (not to mention the time) can be spent on more productive, creative, and valuable activity.

Businesses must adapt to the great changes that have just begun to take shape and embrace the opportunities that technology represents. Because, if history teaches us anything, it is the futility of trying to stem the tide of change.

Source: information-age.com-The robots are coming: better get used to it

RPA and AI are not the future – they are the Now!

Robotic Process Automation (RPA) and Artificial Intelligence (AI) are becoming more prevalent in business and society. As the technology becomes more accessible and efficient, more and more organisations are looking at RPA and AI. Although both of these technologies are not new it does seem that they are now beginning to come of age and radically changing the way the world does business.

So, what is RPA and AI? Let’s consider RPA first of all. Perhaps the most important thing to say about RPA is that it is not a robot! At least it is not a physical robot. RPA is a type of software that is able to interface with computer systems in the same way as a person does. RPA software is able to ‘type’ and is able to ‘click’ and is able to move a cursor. This enables it to open and close programs and to use programs. This is why the term ‘robotic’ was coined – there’s no physical robot but the software behaves in a robotic way. What is key though is that the RPA software is able to carry out tasks with a much greater level of efficiency than a human operator – and it never gets tired.

RPA has been shown to be a highly effective option for carrying out certain types of tasks. It has delivered huge cost savings for organisations and eye wateringly massive returns on investment of 100s of per cent in some instances. It is certainly worth every organisation taking a serious look at how they might take advantage of what it is able to do.

Shop Direct, Telefonica, RAC and nPower are just some of the organisations that have reported substantial benefits to their businesses. Some of those benefits include the reduction of costs of processes. It isn’t however only a matter of cost reduction. Using RPA helps to further improve the quality and consistency of outputs – why wouldn’t it? It also provides organisations with greater auditability / trackability of their processes down to key stroke level. A boon for those in say the financial services sector.

Neither is RPA just about the commercial sector. In 2015, Sefton Council became the first local authority in the UK to trial RPA in its revenues department. At the beginning of the project, leading international service provider, Arvato automated three processes in Sefton’s revenues department to ensure the RPA solution was accurate, robust, auditable and scalable, before extending it to cover a number of high-volume tasks across the department. The tasks vary in complexity, from indexing documents and assigning them to specific workflows to signing up people to direct debit payment of Council Tax and processing discount applications.

Alastair Bathgate, CEO of Blue Prism is confident that RPA has a greater role to play for local government in the future, “We believe there is huge potential for RPA to make a difference in local government thanks to the large number of repetitive back office tasks which can be automated”. His view is support by a a recent study by PricewaterhouseCoopers it was estimated that 45% of work activities could be automated, creating $2 billion of savings in global workforce costs.

RPA is clearly an important tool for organisations to consider. There is though considerable confusion that surrounds it. Many wonder what all the fuss is about given that most organisations already have very high levels of automation and have had for many decades. This gets us to the key to RPA’s appeal. We pointed out that RPA software uses other systems, like a human operator. This is crucial. It means that we can improve the efficiency of a process that is largely automated without necessarily having to make any changes to the existing legacy systems. For anyone who has wrestled with old legacy systems and over stretched IT teams the prospect of being able to make improvements, without instigating costly and resource hungry IT projects, is a very attractive proposition indeed.

RPA often acts as a link, bridging the gaps between systems or it can act as an effective work around for a system that could not quite accommodate a particular set of tasks. Often these system shortcomings have been addressed by getting people to fill the gap. Not only is this often quite inefficient it also creates mind numbingly dull tasks that someone has to do. RPA offers the opportunity to improve the efficiency of a process, reduce cost and often take away tedious tasks, allowing people to focus on more added value, more highly skilled tasks – like talking to customers.

This takes us nicely to the difference between RPA and AI. RPA is a dummy. It is pretty stupid. It does exactly what it is told to do – exactly. There’s no thinking – no judgement – just a set of rules which it blindly follows. It can only work with structured data. If the task requires working with less structured data RPA is struggling. If the rules for what it needs to do – down to individual key strokes – cannot be defined, then RPA is going to struggle.

Enter Artificial Intelligence. AI does have the capacity to work with less structured data. It can find patterns in data and be programed to make choices. AI can learn, based on what it experiences and that learning can then inform future choices. AI is advancing quickly and has evolved into an incredibly useful tool for organisations. Unstructured data such as emails and phone calls can be sifted with AI programmes by identifying key words or phrases before checking parameters and categorising what is required. Virgin Trains have been using AI for some time now to analyse emails received from customers. They are able to make sense of what the email is about by analysing key words. They are then able to decide to make for example further checks on the validity of the email content by perhaps checking if a specific train journey mentioned in the email actually exists. It might then go on to check if there was any reported issue with that train journey. It can then pass the task on to person who is now able to make a judgement about what needs to happen next having been saved the chore (and the time) of checking key facts.

In some instances AI can be used to help structure data allowing it then to be offered perhaps to an RPA solution to progress further. A combination of AI and RPA can potentially transform a process, massively reducing costs through reducing FTE’s while being more efficient and effective at completing tasks than human employment.

What has happened alongside the growing popularity of exploring and implementing RPA and AI is a growing appreciation of not only the benefits of these solutions but also the challenges. Understanding implementation and the processes that RPA and AI can improve is crucial to getting the best return on your investment. There has perhaps been a view that RPA certainly could be almost bought off the shelf and implemented by a school leaver with a GCSE in woodwork. The reality is somewhat different. More people are recognising that there is in fact a lot to consider to get the most from RPA. How to choose the best processes to RPA. How to gain buy-in and support. How to design the new target operating model. What software to choose. How to manage long term. How to ensure the fit with IT . How to set up effective governance.

RPA and AI are not the future, they are the present. A great return on your investment that efficiently and effectively gets the job done. Whether or not you and your organisation ultimately invest in RPA and AI solutions importance of investing in finding out more about it the case for investing some time and energy in finding out more about it and how it might add value to your business is extremely compelling. Those that don’t run the risk of missing out on a very good thing.

Source: sourcingfocus.com-RPA and AI are not the future – they are the Now!