AI: What it Can Bring and How to Prepare for the Future

Every decade a major disruption has occurred that altered the digital landscape: from the PC revolution, to the internet boom, to the mobile-first rise. Each development brought powerful opportunities for businesses that were smart enough to change. So what is next? The artificial intelligence (AI) boom is upon us and technology driving AI is becoming more accessible and affordable for businesses, opening doors for new use cases and workforce augmentation.

By the year 2020, if you aren’t AI-first, it will be too late, much as it was for any business that failed to make the leap to digital in decades past. Organizations have a brief window to experiment and become familiar with the strategies and technologies to get ready for the AI-first world. The emerging AI-first era is already creating new ways for organizations to interact with, serve, and empower customers and employees. For example, by augmenting employees’ capabilities using AI-specifically across intelligent automation, Robotic Process Automation (RPA) and physical automation-organizations will enable workers to achieve far more, faster, with intelligent action and better results.

Additionally, as cloud, big data, and mobile continue to converge, AI-driven user interfaces will lead to ever-deeper, more meaningful interactions-a “situational centricity” tailored not only to each individual customer or employee, but also to his or her unique situation.

An augmented workforce powered by AI will help organizations attract and retain new generations of workers

Currently, there are five actions that companies can take to survive and thrive in the new AI-first era:

1. Embrace AI as the new experience layer: Customers won’t just be on apps or the internet. They will expect AI-powered assistants and invisible user interfaces, as well as differentiated experiences such as voice, mixed reality, and haptics.

2. Augment your workers: The gains we’ve made from innovating workplace productivity have hit a plateau, but AI will help organizations reach new levels of efficiency and effectiveness. An augmented workforce powered by AI will also help organizations attract and retain new generations of workers.

3. Plug in to the Platform Economy: Organizations must be ready to create and join the AI-driven borderless platforms in their industry-and others-in order to reach customers where they want to be.

4. Take a DesignOps approach, everywhere: Combining design thinking and modern engineering principles will be necessary to the digital enterprise’s transformation as a completely user-centric entity. Organizations should start now to build up a culture, mindset, and business model ready for a DesignOps revolution-where everyone is focused on the user and value.

5. Act with responsibility and plan for secondary consequences: The rise of AI is fundamentally changing everything about the way we live, work, and understand our world. Organizations must develop a digital ethics framework that addresses issues like data security, trust and privacy, and provides guidelines about how data should be obtained and used.

As companies move down the path to digital transformation, there is a growing need for organizations to act with responsibility and adopt digital ethics as every digital action can have an equal and potentially unintended consequence. The rise of AI is fundamentally changing the way we live, work, and understand our world, and this “digitization of everything” requires a new level of corporate accountability. Just because something can be done with digital innovation doesn’t mean that it should. Each organization must be prepared to continuously assess how smart machines and humans can best work together to drive productivity and innovation. To maintain the trust of employees, partners and customers, investment and focus is required now to address the ethical issues arising from smart machines in the workplace.

Source: it-services.cioreview.com-AI: What it Can Bring and How to Prepare for the Future

How AI Is Changing The Way Companies Are Organized

Artificial Intelligence may still be in its infancy, but it’s already forcing leadership teams around the world to reconsider some of their core structures.

Advances in technology are causing firms to restructure their organizational makeup, transform their HR departments, develop new training models, and reevaluate their hiring practices. This is according to Deloitte’s 2017 Human Capital Trends Report, which draws on surveys from over 10,000 HR and business leaders in 140 countries. Much of these changes are a result of the early penetration of basic AI software, as well as preparation for the organizational needs that will emerge as they mature.

“What we concluded is that what AI is definitely doing is not eliminating jobs, it is eliminating tasks of jobs, and creating new jobs, and the new jobs that are being created are more human jobs,” says Josh Bersin, principal and founder of Bersin by Deloitte. Bersin defines “more human jobs” as those that require traits robots haven’t yet mastered, like empathy, communication, and interdisciplinary problem solving. “Individuals that have very task-oriented jobs will have to be retrained, or they’re going to have to move into new roles,” he adds.

The survey found that 41% of respondents have fully implemented or made significant progress in adopting AI technologies in the workforce, yet only 15% of global executives say they are prepared to manage a workforce “with people, robots, and AI working side by side.”

As a result, early AI technologies and a looming AI revolution are forcing organizations to reevaluate a number of established strategies. Instead of hiring the most qualified person for a specific task, many companies are now putting greater emphasis on cultural fit and adaptability, knowing that individual roles will have to evolve along with the implementation of AI.

On-the-job training has become more vital to transition people into new roles as new technologies are adapted, and HR’s function is quickly moving away from its traditional evaluation and recruiting function—which can increasingly be done more efficiently using big data and AI software—toward a greater focus on improving the employee experience across an increasingly contingent workforce.

The Deloitte survey also found that 56% of respondents are already redesigning their HR programs to leverage digital and mobile tools, and 33% are utilizing some form of AI technology to deliver HR functions.

The integration of early artificial intelligence tools is also causing organizations to become more collaborative and team-oriented, as opposed to the traditional top-down hierarchal structures.

“To integrate AI, you have to have an internal team of expert product people and engineers that know its application and are working very closely with the frontline teams that are actually delivering services,” says Ian Crosby, cofounder and CEO of Bench, a digital bookkeeping provider. “When we are working AI into our frontline service, we don’t go away to a dark room and come back after a year with our masterpiece. We work with our frontline bookkeepers day in, day out.”

In order to properly adapt to changing technologies, organizations are moving away from a top-down structure and toward multidisciplinary teams. In fact, 32% of survey respondents said they are redesigning their organizations to be more team-centric, optimizing them for adaptability and learning in preparation for technological disruption.

Finding a balanced team structure, however, doesn’t happen overnight, explains Crosby. “Very often, if there’s a big organization, it’s better to start with a small team first, and let them evolve and scale up, rather than try to introduce the whole company all at once.”

Crosby adds that Bench’s eagerness to integrate new technologies also impacts the skills the company recruits and hires for. Beyond checking the boxes of the job’s technical requirements, he says the company looks for candidates that are ready to adapt to the changes that are coming.

“When you’re working with AI, you’re building things that nobody has ever built before, and nobody knows how that will look yet,” he says. “If they’re not open to being completely wrong, and having the humility to say they were wrong, we need to reevaluate.”

As AI becomes more sophisticated, leaders will eventually need to decide where to place human employees, which tasks are best suited for machines, and which can be done most efficiently by combining the two.

“It’s a few years before we have actual AI, it’s getting closer and closer, but AI still has a big problem understanding human intent,” says Rurik Bradbury, the global head of research and communication for online chat software provider LivePerson. As more AI software becomes available, he advises organizations to “think of those three different categories—human, machine, or cyborg—and decide who should be hired for this job.”

While AI technologies are still in their infancy, it won’t be long before every organization is forced to develop their own AI strategy in order to stay competitive. Those with the HR teams, training program, organizational structures, and adaptable staff will be best prepared for this fast-approaching reality.

 

Source: Fast Company-How AI Is Changing The Way Companies Are Organized

10 Success Factors for Deploying Software Robots in the Enterprise

The implementation of software robotics and smart technologies frees a workforce from routine tasks while improving efficiencies, data accuracy and compliance.

Make Sure IT Is Involved from the Start

There often is tension between what IT resources a company’s lines of business need to operate most effectively and the allocation of said resources. While the overarching mandates are to improve service and reduce costs, the resources and priorities of the two groups often are misaligned, constraining business growth and performance. Many RPA implementations emanate from business operations teams, leaving IT on the sidelines in favor of speed and creating shadow RPA projects outside of IT’s oversight. This is a mistake. The most successful, scalable deployments of RPA are implemented in full collaboration with IT leadership.

IT Must Demonstrate its Willingness to Collaborate

It also is important for IT and the business teams to work on the same page. IT must recognize the urgent need for RPA in the business in terms of mandates to improve efficiencies, improve customer satisfaction and other drivers and offer appropriate levels of support and partnership to avoid shadow deployments. Collaborating and agreeing on priority deployments upfront will alleviate alignment issues later.

Begin with an Automation Strategy that Sets Direction

One way to align priorities for the business is to work together on setting and aligning expectations with a common vision. Beginning this process with a documented automation strategy is important. What is the target state of RPA within the operations team? What does the roadmap look like? Establish executive sponsorship upfront, agree to the scale of investment and quantify the expected benefits of that investment so it can be measured. Also consider including a proof of concept or pilot project that supports the defined strategy and vision.

Identify Ideal Process Candidates for Automation

For most businesses, the best candidates for automation often are back-office processes wherein the goal is to provide faster, easier service to customers—such as activating a new SIM card in five minutes rather than 24 hours. These processes are mundane and require entering repetitive data into multiple systems that don’t talk to each another. The goal is not to reduce jobs, but to minimize mundane tasks so people can focus on more value-added and fulfilling work.

Don’t Stop with Quick Tactical Wins

You’ve likely identified a large number of existing processes that can be improved with automation. You can move to automate those quickly, secure wins and demonstrate the success of RPA. But RPA presents an opportunity to drive transformational change in your business. Now is the time to take a step back and allow teams to imagine what is possible. Brainstorm with different groups within the business and allow them to be creative in identifying game-changing and high-impact opportunities to create competitive advantage. What would your business do if time, people and resources were unconstrained?

Choose the Right RPA Technology To Enable Process Automation

As business-line and IT leaders work together to choose the right RPA solution, it’s important to understand the difference between simple desktop scripting, software development kits (SDKs) and enterprise RPA. A desktop automation solution offers a quick solution for a team with short, recorded and replay tactical automations aimed at navigating systems on the desktop. Automated tasks, often manually triggered, are coded or recorded individual keystrokes of a user. They are not connected to enterprise systems and are often deployed without the knowledge of IT. SDKs give IT a better, faster way to deliver on business teams’ expectations, but often don’t involve the operations teams in the process.

Make Security a Key Requirement for Vendor Selection

Business and operations leaders should engage IT early on in the process to ensure proper security, infrastructure and support. Enterprise-class RPA should be deployed in the data center or in the cloud, but never on the desktop. If there is a record button on the desktop, IT can’t monitor or provide security or meet regulatory requirements. Desktop deployments should scream “shadow RPA” to the IT organization. It’s important to ensure RPA software meets required compliance requirements such as PCI-DSS, HIPAA and SOX to provide the necessary security and governance.

Find a Strong Implementation Methodology

There are well-defined methodologies that already have been tried and tested for implementing software robots in the enterprise. Make use of these in your environments: 1) Identify the processes that are best-suited to robotic process automation; 2) Establish the benefits case for robotic process automation, encouraging organization wide recognition and adoption; 3) Implement the required infrastructure, governance and support framework to enable a robotic process automation capability to run efficiently and effectively; 4) Define a best-practice approach for process configuration, which increases the potential for automation and accelerates the development life cycle; and 5) Provide the necessary skills to operational resources via a role-based training and mentoring accreditation program.

Welcome ‘Bots’ to Workforce with Change-Management Best Practices

Both IT and business operations should incorporate change management best practices when introducing software robots as part of the workforce to bring teams along with the vision. Introducing bots into the workforce is new and different, and it requires careful concept selling and implementation. Sharing the company’s vision for how the software robots will add value and improve the business is important, but it’s equally important to help employees understand what’s in it for them: How will these robots help them do their jobs better and more efficiently?

Measure Impact to Demonstrate Value

When helping teams understand the total value of RPA, calculate expected benefits across shareholders, customers and employees. Focusing on one area only will sell the initiative short and miss an opportunity for driving broader enterprise value and scale. Use your RPA software to collect meaningful business intelligence data and real-time operational analytics to report on decisions and actions taken by each software robot. Use this data to see how the organization is performing, where process improvements can be made and what new opportunities for revenue and customer satisfaction can be identified.

Source: eweek.com-10 Success Factors for Deploying Software Robots in the Enterprise

A look to the future with Professor Leslie Willcocks: RPA and the changing world of work

With 2017 fast approaching, a glance at the future seems only appropriate. In our exclusive interview with Professor Willcocks we look ahead in two areas: the future of utilising RPA (Robotic Process Automation) and its implications to the market at large.

Past November Digital Workforce organized a unique breakfast seminar discussing the role of RPA in digital strategy and excitedly welcomed the event’s keynote speaker, Professor Willcocks. Leslie Willcocks, a professor of London School of Economics, is considered one of the world’s most respected researchers, speakers and business publications writers in the field of knowledge work automation. Following the seminar, Professor Willcocks sat down in private to answer some of our questions.

The larger value of RPA is tied to business processes and institutionalization of the technology. How do organizations reach these benefits as they move forward with RPA?

“One of our researched organizations had an interesting model they worked with, that in my opinion could well be worth coping elsewhere. The company had identified eight key in-house competences which they combined with client assets to form a third entity – a service delivery vehicle. One of the organization’s key competences was process re-engineering, an area in which Robotic Process Automation falls perfectly.

RPA isn’t a technology in a vacuum. It has to sit with something and it fits process best, but the technology has to sit with people too. This is a late learning, as the early adopters often focused on fixing individual processes; almost like sticking a plaster – though a good one – on a wound. Fixing individual processes offers limited benefits compared to adopting the technology on a strategic scale, but doing so requires willingness to build new capabilities. Luckily we found, that all good process principles, such as Six Sigma and Lean, fit RPA extremely well – these principles demand companies to take a broader look at their business strategy and key performance indicators as well as consider their alignment with the organization’s process technologies and people. New adopters of RPA are doing exactly this.”

Considering future advances, could RPA be utilized to tap into even more opportunities?

“RPA technologies are one small piece of the bigger automation jigsaw. Digitalization should be looked at as a whole. The organizations I know of work with automation centers of excellence. This should be the approach even if RPA is the only tool in the box right now. Things like business analytics and amplifying automation by analyzing unstructured data with solutions such as cognitive intelligence stick on top of what can be done with RPA. Creating a platform compatible for integrating all these solutions should be the obvious next step.”

What kind of impact do you expect RPA will have to the market at large?

“Compared to other robotic technologies RPA faces less issues related to ethical conflicts or underdeveloped regulations. On the contrary, RPA is often used to conform with regulatory requirements. It is however, important that the modern tech area is well regulated. Having regulations in place helps steer the impact of fast moving change while the social implications of growing business efficiency depend on the power and wealth being spread fairly.

Studies suggest jobs being both created and lost as a result of RPA automation. There is also a distinct difference between using a technology as a complementary or replacement solution. The full data is poorly incorporated to most studies. Such flawed publications speak of 47% job loss due automation. Based on our research, 14-16% fewer jobs in the sectors where RPA operates seems realistic. However, the most of the eliminated work load won’t translate to loss of total jobs but partial jobs.

Using the term “robot” seems sometimes unnecessarily bias, when you consider that RPA could just as well be described as a software solution. When describing RPA I often use the line “taking the robot out of the human” as it accurately describes what the technology does. The amount of knowledge work has dramatically increased in every sector from health care to banking. Over the last 10 years of conducting interviews, no one has ever told me that their work load has stayed the same or decreased! This fact has gone largely unnoticed in the public discussion but resulted to a situation where, for all the over-worked individuals, implementing RPA is simply great!”

Source: digitalworkforce.eu -A look to the future with Professor Leslie Willcocks: RPA and the changing world of work

Clear goals, patience required for successful IT automation strategy

More companies are investing in automation to streamline processes. But for an IT automation strategy to be successful, it’s important to start with clear, well defined goals.

“Automation” is a scary word for many IT workers — who contemplate images of robots, software and the like stealing their jobs as it becomes the norm.

But according to speakers at the annual Automation Innovation conference in New York last month, the short-term goal for an IT automation strategy should be to empower knowledge workers — not simply replace them.

“If you do the integration and infusion [of automation technology] correctly, you will expand [knowledge workers’] capabilities; you will not detract from them,” said conference speaker R.G. Conlee, CIO of Conduent. “We are not out to just replace people.”

More than 300 attendees packed the Bohemian National Hall in New York City for the conference to discuss IT automation strategy and potential roadmaps to make this strategy successful. Conference organizers noted that the goal was to help attendees “transition from traditional labor to RPA, intelligent automation and cognitive computing.”

But to realize the great business potential of IT process automation and attain a positive return on investment, it’s important to start with concrete goals such as improving price points or a particular process.

“It pays to focus on a specific purpose for automation rather than thinking of it as a broad platform with extended capabilities,” said Bill Galusha, senior product marketing manager of software provider Kofax.
Automation innovation challenges

Conlee noted that many companies have experienced “digital disillusionment” when it comes to the latest technological fads. CIOs and other members of the C-suite, have gotten tired of chasing the latest shiny new technological toy, Conlee said, and are seeking definitive results from these investments.

“They are saying we want it to be practical, something we can use, and we want it to make a difference,” Conlee said. “In other words, we want to improve the way work is done; we don’t just want new ways of doing the work.”

It’s important to remember that moving to automation takes patience, Conlee added, because many IT and digital systems actually negatively impact productivity while they are being integrated with company processes. Implementation of automation is a big challenge, and a plan is required that takes speed to market and complexity into consideration, he added.

We want to improve the way work is done; we don’t just want new ways of doing the work.

“There is a training curve for digital systems that does not elicit better work in the short term; it takes time to get there,” Conlee said.

An IT automation strategy can be a huge help when it comes to one common issue facing modern digitized companies, Galusha said: process and data complexity. Because these companies are responsible for many systems with numerous internal/external data sources, it is difficult to connect all that information to the company’s processes.

A robotic process automation strategy can help with consolidating data for analytics purposes, Galusha said, and apply unique business rules to information contained in these numerous data sources.

“Your processes, and how you are making decisions, [is] only as good as the information,” Galusha said. “If you are doing it manually, it’s slow, it’s inefficient, and you’re probably making errors along the way.”

Galusha was quick to point out that obstacles to the automation revolution remain. Robots still have difficulty with distinguishing visual content such as invoices, purchase orders and email correspondence, for example.

“We also have to understand the complexity, really understand the use cases and how more sophisticated learning technology can be applied,” Galusha said.
IKEA’s automated customer service

Speakers at the conference also noted that automation will bring cost savings in the long run, but it could also expand business opportunities and help provide better premium service to customers. One company that is seeing these types of benefits is IKEA, which uses process automation to improve customer experience and engagement.

Martijn Zuiderbaan, Solution Owner at IKEA Retail AB, noted that IKEA is responsible for its entire supply chain, so prior to its implementation of automation, there were several potential areas that could have benefitted from it. The company decided to start small, by implementing automation processes into its customer call centers, with the goal of making its online customer service more efficient, engaging and effective.

“I think most enterprise companies are working towards a perfect future where all their solutions can talk to each other and everything works together, communicates and shares data,” Zuiderbaan said. “The reality is not really there.”

IKEA receives 20 million customer inquiries per year via voicemail, chat, mail and social media, Zuiderbaan said. The company is using automation to keep up with this demand and help it engage with customers in a smarter way.

In short, Zuiderbaan said the automation solutions were used to meet IKEA’s need to bridge gaps in the existing IT solutions to improve both customer and worker experience at the furniture giant.

“We tried to be more efficient, we tried to make our co-workers more engaged, and we tried to make work more effective,” Zuiderbaan said of IKEA’s automation efforts. “By combining these three, we tried to get a better customer experience.”

Source: searchcio.techtarget.com-Clear goals, patience required for successful IT automation strategy

How Can The CIO Drive RPA As A Strategic Imperative?

The use of Robotic Process Automation, using concepts such as software bots, is emerging, but its use can’t succeed in isolation. The CIO needs to get involved to implement an enterprise strategy.

In recent years, Robotic Process Automation (RPA) has emerged as an effective enabling technology to gain efficiencies by automating repetitive, rule-based, manual tasks and mitigating human error risks.

For example, AT&T has established and grown a footprint of 200 software bots across its customer service organization, a capability that emerged out of an innovation center. Now, launched as a simple-to-use, cloud based enterprise technology, these software bots can be used by any AT&T employee to automate manual work.

The growth projections for RPA have created a fair amount of excitement. Spend on RPA tools and services is expected to grow at 60% annually over the next five years according to a new market report published by Transparency Market Research. However, the RPA growth story has its challenges. While we continue to see initial interest and pilot initiatives amongst buyers to test automation technologies, some struggle to grow initial success into an enterprise level capability.

Even for buyers that have successfully executed automation initiatives, growth may be difficult to sustain with sporadic, stand-alone deployments across multiple business functions.

Proactive IT involvement is essential to RPA’s emergence as a strategic capability. Many business teams have eagerly adopted RPA due to its non-intrusive automation approach and minimal impact to current IT systems. However this move often results in marginalizing the IT team’s involvement in such initiatives. Further, CIOs across industries have been largely dismissive of RPA as a tactical short-term fix, ultimately to be usurped by traditional IT transformation or Business Process Management Suite (BPMS) projects.

There is a clear need for change, as IT has a pivotal role to play in growth of RPA as a strategic enterprise competency. CIOs must define the automation strategy for their organizations by developing a better understanding of the business requirements and driving RPA as an enterprise level capability—not dissimilar from the way cloud technologies have evolved in the last few years. Here are three steps for CIOs to consider:

1. Partner with business to be a trusted solution advisor. Business users can clearly define their automation needs, but RPA may not be the right answer in all situations. Some requirements can be better addressed with IT transformation or BPMS, and only IT can help make these crucial decisions. Also, regardless of the “light automation” offered by RPA solutions, a host of other IT considerations need to be factored in. Impact to existing security protocols and any possible risks to business and data due to automated processing need to be assessed carefully. Use of RPA software can increase transaction load on existing applications (robots work relentlessly, often drastically increasing productivity and system workload), posing the risk of unplanned downtime and wasteful use of support resources to recover crashed applications. As RPA solutions scale up from tens to hundreds of robots across the organization, adequate infrastructure and network capabilities need to be provisioned with well-defined contingency plans. Such issues can be addressed effectively only if the CIO’s organization gets involved upfront, develops a clear understanding of the business requirements, and proposes the right solution and implementation approach.

2. Select an enterprise-level platform to build RPA capability. As multiple individual functional owners experiment with automation, technology choices are seldom made cross-functionally. This could result in multiple RPA platform deployments across the organization, making it difficult to manage and scale automation and deliver a real enterprise capability to the overall business.

Organizations need to make the platform choice at an enterprise level, and no function is better positioned than IT to drive that decision. IT can conduct a thorough evaluation of technical capabilities and architectural considerations, including performance and reliability of the software, change control, access management, maintenance requirements and integration capabilities. For example, the platform should be able to easily setup a library of services that can be used to integrate with the existing application portfolio. By gaining a deeper understanding of business requirements, IT can make an informed choice of a platform that’s easy to manage and control. There are financial benefits from an enterprise level decision too, better pricing and contractual terms as compared to function-level deployments.

3. Establish an RPA Center Of Excellence (COE). The COE approach is fast emerging as the recommended operating model to grow an RPA footprint in medium and large enterprises. In one example, a financial services organization successfully launched a pilot project in 2008 to automate their claims receipt and adjudication processes, long before RPA became an industry buzzword. By launching an automation COE thereafter, this organization has successfully expanded RPA capabilities to several hundred bots operating across its domestic and international delivery centers.

Investment in a COE can help organizations to better manage requirements and deliver efficient automation solutions by:

  • Leveraging best practices and implementation experience to deploy RPA where it is the most effective choice for automation
  • Establishing a sustainable governance model to identify and qualify RPA opportunities, and to deploy and stabilize RPA solutions
  • Instituting an “asset management” approach to manage RPA deployments — For example, if RPA solutions become redundant to a particular function due to an IT project, the COE can re-use the technology for future initiatives elsewhere
  • Tracking, monitoring and reporting process improvements and financial benefits across the enterprise.

Such a COE should be staffed with both technical and functional resources, including RPA solution developers, project managers, process SMEs and business analysts, along with cross functional representation from human resources and procurement. Careful consideration should be given to whether the COE should be aligned to the CIO, even though conventional thinking suggests automation efforts have better likelihood of success while reporting to the business.

Ultimately, RPA’s light automation approach is here to stay, but its emergence as a strategic capability is contingent to the CIO’s office coming on board. Functional owners can take the initial baby steps, but IT can help take it to the next level with enterprise-grade results.

Source: informationweek.com-How Can The CIO Drive RPA As A Strategic Imperative?

What is Robotic Process Automation, and what benefits could it bring to your enterprise?

What is the key to making Robotic Process Automation a success? HCL Technologies’ Kalyan Kumar looks at how business can benefit from leveraging the power of AI and automation.

It’s an age-old problem for the C-suite to solve: how do you do better and do more with less? Having invested in technological advances such as cloud and digitalisation over the last few years, many businesses are now at the part of the roadmap where they have budgeted for spend to level-out, and the forecasted benefits to roll in. However, investment is still needed in most cases, so how can enterprises continue to build when the resources available to them have ceased to grow? The answer is getting technology to lend even more of a helping hand than it is currently doing, in the form of analytics and Artificial Intelligence (AI) integrated Robotic Process Automation.

What form will Robotic Process Automation with AI take in the business arena?

On a practical level, Gartner says AI will manifest itself in the continued rise of the ‘smart machine,’ something it predicts to be one of the biggest technology trends over the coming decade. It says enterprises will increasingly draw on growing computing power and ever-increasing sources of data to adapt to new situations, solve problems and ultimately get ahead of the competition. One of the key ways that they can do this is by automating routine processes and using AI, so that the efforts of skilled employees can be redirected to areas that will be more beneficial to the business than ever before.

This is where Robotic Process Automation (RPA) with AI comes in, enabling business and IT teams in an enterprise to automate processes using a virtual software robot. This robot interprets activities and stimuli within the business and then responds with an appropriate action, based on the parameters defined by the business. In effect, RPA with AI emulates a human operator, or acts as a tool to carry out repeatable processes or tasks. For example, it could be used by a bank to auto-complete registration forms when processing a higher than expected number of applications for a recently-launched type of account. Firms in a range of other sectors could also enjoy the benefits of being able to handle a sudden peak in inbound calls using of a virtual service desk employee to route inquiries more efficiently.

Reaping the benefits

Businesses will benefit greatly from having functions and processes automated at scale, and with repeatability. In addition to bringing potential cost reductions, RPA can also streamline processes and enhance the overall end-user experience. There are four big benefits enterprises should be able to draw from this:

  • A more consistent experience than ever before. With robots following specific formulae and layouts, and performing at a uniform speed, a standard level of output should be more achievable than ever before.
  • Deeper insights into business / IT performance and customer experience.
  • A reduction in the level of human error. We all become fatigued and make mistakes on occasion; this potential for error is limited by the use of RPA.
  • More speedy execution than ever before, with some areas of the business able to run 24/7. This means enterprises will be in a much better position to keep things moving even when it’s the end of the working day for its human employees.

Is it for everyone?

As with the adoption of any new kind of technology, enterprises must build a realistic business case for Robotic Process Automation before taking the plunge, or it could just be a wasted effort. This means taking the time to map out costs and expected benefits before budgets can be assigned and work can get underway. The key to making this work is thinking about RPA with analytics and AI from a wider strategic perspective: it’s no good just making vague statements about the potential benefits it can bring. Be clear on exactly what the end goal is, and how it will bring improvements to different existing processes within the business.

Once funds have been secured, businesses must develop a clear idea of the internal processes that are already running: what duty does everything perform, and what does it connect with? As the wires can become increasingly tangled here, it goes without saying that processes that have not previously been integrated and automated in the past will be much easier to improve through the use of RPA. Businesses will also need to consider how processes that are supported by their legacy IT systems will be impacted, as it will be much more difficult to integrate Robotic Process Automation with older technologies. The good news is that it is relatively simple to integrate RPA with existing automation and orchestration platforms, so those that have already invested in machine learning technologies may have much of the groundwork already in place.

Success as part of the wider picture

It’s also important to realise that the benefits won’t be so great if you’re automating a
single or standalone process. To be truly effective, RPA must be integrated with a complete service delivery chain to streamline the entire process, rather than just one small part of it. Furthermore, when Robotic Process Automation is integrated with Cognitive/Machine Learning capabilities, it will be able to learn to complete new processes and functions by itself, which is where it will really start to have a positive impact for the workforce.

The key to making RPA a success is taking the time to ensure it is embedded deep within existing systems and business operations. By skipping that stage, there is the risk that RPA will be tacked on simply for its own sake and is unlikely to deliver the benefits it can provide. If they get it right however, enterprises will be perfectly placed to leverage the power of AI and automation to accelerate the adoption and dynamic adjustment of process change in the digital world, proving a real springboard to success for the 21st Century enterprise.

Source: cbronline.com -What is Robotic Process Automation, and what benefits could it bring to your enterprise?

Automation + Jobs: Not a Zero-Sum Equation

There’s been no shortage of hand wringing over the job costs of automation—and it’s not without cause. Automated devices are increasingly replacing people in all sorts of occupations. Just as a long list of other technologies have done before. Because dramatic workplace transformations do not occur often, it’s easy to see such shifts as zero-sum occurrences and overlook the new options presented as the familiar ones fade away.

The last time such a major shift took place was during the transition from an agricultural-based economy to an industrial-based economy. And though the tractor and other automated farm equipment did put many farmers and other agricultural workers out of work, people did successfully make the shift. This example has been used so frequently and is so far removed from our current reality that many dismiss this comparison and say that the disruption being brought by automation today is different from the change brought by automation to farming a century ago.

David Autor, an economist who assesses the labor market consequences of technological change and globalization, disagrees. In a recent TedTalk to explain why automation does not just eliminate jobs, Autor highlighted an interesting employment development that has taken place in the banking industry since the advent of the ATM. In his presentation, Autor said: “In the 45 years since the introduction of the automated teller machine…the number of human bank tellers employed in the United States has roughly doubled, from about a quarter of a million to a half a million. A quarter of a million in 1970 to about a half a million today, with 100,000 added since the year 2000.”

Though the number of tellers per bank dropped by roughly a third due to the ATM, banks also discovered that, as a result of the ATM, it was less costly to open new branches, said Autor. He added that the number of bank branches has increased about 40 percent since the appearance of the ATM. That’s why there are more tellers now than there were before ATMs replaced so many of them.

Of course, tellers today do different work than they did historically. “As their routine, cash-handling tasks receded, they became less like checkout clerks and more like salespeople, forging relationships with customers, solving problems and introducing them to new products like credit cards, loans and investments,” said Autor. The tellers are now performing “a more cognitively demanding job.”

The same thing has been happening in the manufacturing and processing industries for decades now. While automation has eliminated many industrial jobs, it is also largely responsible for the plethora of industrial jobs that have been coming back to the U.S. It’s also the reason so many new manufacturing jobs are starting here rather than elsewhere. But today’s manufacturing jobs—just like today’s bank teller jobs—are clearly different from what they used to be. Autor pointed out, “As our tools improve, technology magnifies our leverage and increases the importance of our expertise and our judgment and our creativity.”

In the interim phase we find ourselves in—between manufacturing’s past and its future—we face a challenge. A challenge we have faced before. The last time was a century ago, during the transition from the agricultural economy to an industrial one. As automation was eliminating agricultural jobs, the farm states “took the radical step of requiring that their entire youth population remain in school and continue their education to the ripe old age of 16,” said Autor. “This was called the high school movement, and it was a radically expensive thing to do. It also turned out to be one of the best investments the U.S. made in the 20th century. It gave us the most skilled, the most flexible and the most productive workforce in the world.”

Autor pointed out that, when surveying our current industrial employment situation with an eye toward correcting its current course, “It’s foolish to say there’s nothing to worry about. Clearly we can get this wrong. If the U.S. had not invested in its schools and in its skills a century ago with the high school movement, we would be a less prosperous, a less mobile and probably a lot less happy society. But it’s equally foolish to say that our fates are sealed. That’s not decided by the machines. It’s not even decided by the market. It’s decided by us and by our institutions.”

Given the current state of political matters in the U.S., it’s clear than any large scale, government-driven support for an educational solution—like the one Autor referenced—is highly unlikely. However, action is being taken on a smaller scale in localized areas, such as in Ohio and Indiana, and even in the manufacturing corridor in upstate South Carolina. Despite such positive actions by many of our institutions, the scale of the problem will require additional help from the automation industry and its manufacturing customers.

An example of how automation suppliers are taking action can be seen in Festo’s efforts to bring the German apprenticeship model to the U.S. Yaskawa is another automation technology supplier stepping up to the plate to address the automation-versus-jobs issue through its robotic training programs.

Having seen his former aerospace manufacturing employer go through massive layoffs in the mid-1990s—reducing its workforce by more than 60 percent in three years—Buddy Smith, who is now manager of the Yaskawa Academy for Yaskawa America, knows firsthand how technology suppliers and their manufacturing customers can play a more active role in improving today’s manufacturing workforce situation.

“If a manufacturer of any size decides to add robots to its workforce,” said Smith, “the company’s owners and executives can and should prepare the workforce in advance. There are a lot of communication opportunities to start a dialogue with workers. For example, explain why robotics will help workers, boost production and increase profit sharing. When a company capitalizes on these opportunities, it creates excitement by outlining how robotics can open doors to new training, provide a chance to tackle new responsibilities and reduce injuries.”

To help manufacturing customers who have purchased a robot communicate more effectively with their workers, Smith explained Yaskawa Motoman offers customers a range of robotics classes covering everything from programming to maintenance. “For our maintenance training, a student can spend one week with us and learn about 85 percent of what they’ll face on the job. That’s a terrific example of how retraining an already-employed worker can give them new skills and reap rewards for his or her employers,” he said.

Smith noted that different companies will, of course, have different workforce needs. For example, a large manufacturer may already have some technically inclined workers on staff who “could transition easily into robotics training,” he said. A small job shop, however, may need to look outside its walls to hire a robotics-qualified employee.

“Each company has to think about how to get a return on its robotics investment,” Smith said. “Improving production is not just about purchasing a robot. It’s also about weighing the decision to bring in someone skilled at programming a robot or retraining an employee to program and work with a newly purchased robot. Ultimately, though, the answer is not really a choice between retaining, retraining or recruiting. The solution is a mix of these things depending on the company’s position.”

Source:  automationworld-Automation + Jobs: Not a Zero-Sum Equation

Bring on the Bots

Artificial intelligence is moving from science fiction to practical reality fast.

AI — technology that teaches machines to learn so they can perform cognitive tasks and interact with people — is suddenly accessible to many companies. Costs associated with the advanced computing and data-storage hardware behind AI are plummeting. A growing number of vendors also offer AI tools such as robotic processing automation that can be configured without the help of a rocket scientist.

So this is clearly an area more banks will need to pay attention to going forward.

Already some AI pioneers have emerged in the financial industry just over the past year: Bank of New York Mellon‘s use of robotic process automation in trade settlement and other back-office operations; Nasdaq‘s search for signs of market tampering with an assist from AI; UBS’ initiative to answer basic customer-service questions through Amazon’s virtual assistant, Alexa; and USAA‘s development of its own virtual assistant.

Most large banks are considering using AI wherever mundane or repetitive tasks could be offloaded to a computer fairly easily.

What It Can Do

Here are some examples of where AI could make the biggest difference.

Customer conversations. Chatbots, natural language processing and speech processing could all be used to improve social interactions. In addition to USAA, Bank of America, Capital One Financial, Barclays and BBVA are experimenting with AI-powered virtual assistants.

“The vision that excites me is the one where we have seamless interactions, where I’m interacting with people, with the bank, with systems in the bank, and at the end of the day what the bank is giving me is exactly what I want,” said Marco Bressan, chief data scientist at BBVA. “We shouldn’t have a fixed idea of what the customer wants. There are some customers that the less they see their banks the better, as long as their money is well taken care of. Other customers want to see their bank every day. We have to serve both. And communicating with each of those from an AI perspective is very different. One has to do with full automation, and the other has to do with a smart interface.”

Automated investment advice. AI is used to help investment advisers and robo-advisers make better recommendations to customers. Australia’s ANZ Group has been using IBM’s Watson in its wealth management division for three years. Watson can read and understand unstructured data found in contracts and other documents, comb through millions of data points in seconds, and learn how to draw conclusions from the data. It can assess a new customer’s financial situation more quickly and comprehensively than a human being, and it never forgets anything.

BlackRock uses AI to improve investment decision-making. The startup Kensho combines big data and machine-learning techniques to analyze how real-world events affect markets.

Faster, better underwriting. BBVA uses artificial intelligence to improve its risk scoring of small and midsize businesses. “We realized we could update data in real time and integrate it with what the risk analysts were doing to have a much deeper understanding of their own portfolio,” Bressan said.

Some online lenders use AI to speed up their process. The software can look at hundreds or thousands of attributes, such as personal financial data and transaction data, to determine creditworthiness in a split second. The system learns as it goes — when a lender gets payment information on loans, that information gets fed back into the system, so its knowledge evolves.

However, some people question whether AI programs can be trusted to make sound, unbiased lending decisions.

Streamlined operations. BNY Mellon, Deutsche Bank and others are using bots in their back offices to automate repetitive tasks like data lookups.

Assisted account opening. Account origination can be a slow, cumbersome process. Some banks are experimenting with robotically automating some elements, such as data verifications.

Fraud detection. Card issuers and payment processors like PayPal use AI to compare current card transactions to the user’s past behavior as well as to general profiles of fraud behavior. Human analysts teach the model to discern the difference between legal and fraudulent transactions.

General efficiency. “The financial industry is an enormous percentage of the GDP,” said Robin Hanson, an associate professor at George Mason University. “A lot of it is due to various regulations and rules about who has to do what and how. It’s entrenched in regulatory practices, and it’s really hard to innovate in finance because you run into some of these obstacles.”

For example, Hanson wanted to sell some books at a convention. To do so, he had to apply for a tax ID, pay a fee and cover $25 in sales taxes. That required him to go to his bank to get a cashier’s check, for which he had to pay a $5 transaction fee and postage. “That’s an enormously expensive, awkward process,” he said. “If we had an efficient financial system, that would cost pennies.”

Unintended Consequences

As AI is used to improve the speed and efficiency of tasks now performed by humans, there are potential unintended consequences. For one, people in lower-paying jobs in operations, branches, compliance and customer service are likely to lose those jobs.

“Bank executives say they’re going to take those people and put them into high-tech, high-pay jobs to help us code, help us do this, help us do that. It’s just not going to happen,” said Christine Duhaime, a lawyer in Canada with a practice in anti-money-laundering, counterterrorist financing and foreign asset recovery and the founder of the Digital Finance Institute. However, “the bank may end up with the same number of employees,” as it sheds customer-facing jobs and hires trained software developers to code.

There are also privacy concerns around the use of AI in financial services. “From a consumer protection point of view, there are concerns people need to take into account when it comes to AI, machine learning and algorithmic decision-making,” said Steve Ehrlich, an associate at Spitzberg Partners, a boutique corporate advisory and investment firm in New York. “Say a company wants to look at your social media or your search engine history to determine your creditworthiness. They go into Facebook and find a picture of you that you didn’t upload. It’s a picture of you at a bachelor party or gambling at a casino. That data gets fed into the algorithm. For one, they should tell you they were going to be taking that information.”

There is also the chance that bots and AI engines could run amok and make poor lending decisions, or commit an operations error that a human with common sense could have averted.

What Banks Can Do

These caveats aside, banks’ wisest course is to prepare to be part of the revolution.

One thing they can do is create an internal center of excellence where a group of people become experts and help bring AI to other parts of the company. They could test technology and use cases and guide the business units in their adoption of bots and AI. Citigroup and BBVA are among the banks doing this. BNY Mellon has a robotics process automation team that partners with businesses and has come up with eight pilots, including settlement and data reconciliation.

Banks also can try to encourage people to embrace AI — even if their jobs are at risk. It helps to communicate that there could be some benefit to them. “People in operations and data analysts don’t want to be doing this work anyway — swivel-chair work, mindless copying and pasting and keying in data,” said Adam Devine, head of marketing at WorkFusion, a robotics process automation software provider that competes with Blue Prism and Automation Anywhere.

David Weiss, senior analyst at Aite Group, also sees the trend as an eventual positive for employees. “I personally argue for human augmentation — go after the peak human problems first,” he said. “There, you’re not going to cut jobs, you’re just going to make people more functional, and leverage their inorganic intelligence more.”

But there’s no question the workplace will change and people will have to adapt.

Source: AmericanBanker.com-Bring on the Bots

Building a business case for offshore robotic process automation

For years, business case for the offshore captive IT center model — whereby companies set up their own wholly owned IT service centers abroad — has centered on the benefits of labor arbitrage to generate cost savings. However, as the return on salary differentials has dwindled and the pressure on captive centers to create additional value, companies are looking to other sources of lower costs and increased efficiencies.

The current rise of robotic process automation (RPA) presents an opportunity for IT organizations to wring more benefits from their offshore delivery centers. The rapidly advancing technology that is used to automate rules-based and repetitive tasks with limited or no human involvement is growing in popularity among the captive center set, says Sarah Burnett, vice president of research with outsourcing research firm and consultancy Everest Group. RPA offers a number of benefits: incremental cost savings over traditional offshore delivery; improved service delivery in the form of process quality, speed, governance, security and continuity; relatively shorter investment recovery periods; and a general ease of implementation.

CIO.com asked Burnett about the increased adoption of RPA and offshore captive centers, the hard benefits of implementation, and the best way to build a business case for automation in offshore IT delivery centers.

CIO.com: Why are functions that are already offshored ripe for the application of RPA? Are onshore IT and business operations also candidates?

Sarah Burnett: RPA is a no brainer for most transactional services irrespective of whether they are offshored or not. RPA can help lower costs while increasing the efficiency of operations. This can help global In-house centers or shared service centers achieve their year-on-year efficiency targets.

[Our recent research] shows that costs of operations in offshore global in-house centers can be lowered by 20 to 25 percent. The savings would be even higher for onshore centers. RPA can also address specific issues such as shortage of resources and skills and where there is a high rate of staff attrition due to the repetitive and boring nature of transactional work.

CIO.com: You’ve noted that RPA has the potential to reduce headcount by 25 to 45 percent resulting in significant cost savings. Does the business case for RPA need to address more than headcount reductions?

Burnett: Headcount reduction is enough of a factor for some enterprises, but not all automate with that as a top priority. Some want to keep the staff and create capacity for other more complex work or address issues such as an influx of new work. It is also important to note that automation is not just about headcount reduction, but also increased quality and standardization of work.

CIO.com: What are the biggest factors that would impact the business case of RPA in an offshore location?

Burnett: I think increasing salaries and shortage of skills could drive demand for automation. Clients of offshore centers are also driving automation for increased efficiency and throughput. This is part of their continuous and year-on-year improvement. One factor that could adversely affect automation in offshore centers is lack of skills for deployment.

CIO.com: What should organizations consider in order to build a realistic business case for RPA?

Burnett: The existing and potential costs and benefits of all of these [issues] should be factored into the business case. There are costs that are easy to measure, e.g., cost of RPA software licenses. [But] there are also qualitative values, such as reduced error rates, that are difficult to measure but these must be factored in for a comprehensive business case.

CIO.com: What other advice would you offer IT organizations considering implementing RPA in captive centers?

Burnett: It is important to benchmark existing operations to work out the benefits of automation and build a business case for deployment and scaling up.

Source: CIO.com.au-Building a business case for offshore robotic process automation