IPSoft's Amelia

NelsonHall recently attended the IPSoft analyst event in New York, with a view to understanding the extent to which the company’s shift into customer service has succeeded. It immediately became clear that the company is accelerating its major shift in focus of recent years from autonomics to cognitive agents. While IPSoft began in autonomics in support of IT infrastructure management, and many Amelia implementations are still in support of IT service activities, IPSoft now clearly has its sights on the major prize in the customer service (and sales) world, positioning its Amelia cognitive agent as “The Most Human AI” with much greater range of emotional, contextual, and process “intelligence” than the perceived competition in the form of chatbots.

Key Role for AI is Human Augmentation Not Human Replacement

IPSoft was at pains to point out that AI was the future and that human augmentation was a major trend that would separate the winners from the losers in the corporate world. In demonstrating the point that AI was the future, Nick Bostrom from the Future of Humanity Institute at Oxford University discussed the result of a survey of ~300 AI experts to identify the point at which high-level machine intelligence, (the point at which unaided machines can accomplish any task better and more cheaply than human workers) would be achieved. This survey concluded that there was a 50% probability that this will be achieved within 50-years and a 25% probability that it will happen within 20-25 years.

On a more conciliatory basis, Dr. Michael Chui suggested that AI was essential to maintaining living standards and that the key role for AI for the foreseeable future was human augmentation rather than human replacement.

According to McKinsey Global Institute (MGI), “about half the activities people are paid almost $15tn in wages to do in the global economy have the potential to be automated by adapting currently demonstrated technology. While less than 5% of all occupations can be automated entirely, about 60% of all occupations have at least 30% of constituent activities that could be automated. More occupations will change than can be automated away.”

McKinsey argues that automation is essential to maintain GDP growth and standards of living, estimating that of the 3.5% per annum GDP growth achieved on average over the past 50 years, half was derived from productivity growth and half from growth in employment. Assuming that growth in employment will largely cease as populations age over the next 50 years, then an increase/approximate doubling in automation-driven productivity growth will be required to maintain the historical levels of GDP growth.

Providing Empathetic Conversations Rather than Transactions

The guiding principles behind Amelia are to provide conversations rather than transactions, to understand customer intent, and to deliver a to-the-point and empathetic response. Overall, IPSoft is looking to position Amelia as a cognitive agent at the intersection of systems of engagement, systems of record, and data platforms, incorporating:

• Conversational intelligence, encompassing intelligent understanding, empathetic response, & multi-channel handling. IPSoft has recently added additional machine learning and DEEP learning
• Advanced analytics, encompassing performance analytics, decision intelligence, and data visualization
• Smart workflow, encompassing dynamic process execution and integration hub, with UI integration (planned)
• Experience management, to ensure contextual awareness
• Supervised automated learning, encompassing automated training, observational learning, and industry solutions.

For example, it is possible to upload documents and SOPs in support of automated training and Amelia will advise on the best machine learning algorithms to be used. Using supervised learning, Amelia submits what it has learned to the SME for approval but only uses this new knowledge once approved by the SME to ensure high levels of compliance. Amelia also learns from escalations to agents and automated consolidation of these new learnings will be built into the next Amelia release.

IPSoft is continuing to develop an even greater range of algorithms by partnering with universities. These algorithms remain usable across all organizations with the introduction of customer data to these algorithms leading to the development of client-specific customer service models.

Easier to Teach Amelia Banking Processes than a New Language

An excellent example of the use of Amelia was discussed by a Nordic bank. The bank initially applied Amelia to its internal service desk, starting with a pilot in support of 600 employees in 2016 covering activities such as unlocking accounts and password guidance, before rolling out to 15,000 employees in Spring 2017. This was followed by the application of Amelia to customer service with a silent launch taking place in December 2016 and Amelia being rolled out in support of branch office information, booking meetings, banking terms, products and services, mobile bank IDs, and account opening. The bank had considered using offshore personnel but chose Amelia based on its potential ability to roll-out in a new country in a month and its 24x7 availability. Amelia is currently used by ~300 customers per day over chat.

The bank was open about its use of AI with its customers on its website, indicating that its new chat stream was based on the use of “digital employees with artificial intelligence”. The bank found that while customers, in general, seemed pleased to interact via chat, less expectedly, use of AI led to totally new customer behaviors, both good and bad, with some people who hated the idea of use of robots acting much more aggressively. On the other hand, Amelia was highly successful with individuals who were reluctant to phone the bank or visit a bank branch.

Key lessons learnt by the bank included:

• The high level of acceptance of Amelia by customer service personnel who regarded Amelia as taking away boring “Monday-morning” tasks allowing them to focus on more meaningful conversations with customers rather than threatening their livelihoods
• It was easier than expected to teach Amelia the banking processes, but harder than expected to convert to a new language such as Swedish, with the bank perceiving that each language is essentially a different way of thinking. Amelia was perceived to be optimized for English and converting Amelia to Swedish took three months, while training Amelia on the simple banking processes took a matter of days.

Amelia is now successfully handling ~90% of requests, though ~30% of these are intentionally routed to a live agent for example for deeper mortgage discussions.

Amelia Avatar Remains Key to IPSoft Branding

While the blonde, blue-eyed nature of the Amelia avatar is likely to be highly acceptable in Sweden, this stereotype could potentially be less acceptable elsewhere and the tradition within contact centers is to try to match the nature of the agent with that of the customer. While Amelia is clearly designed to be highly empathetic in terms of language, it may be more discordant in terms of appearance.

However, the appearance of the Amelia avatar remains key to IPSoft’s branding. While IPSoft is redesigning the Amelia avatar to capture greater hand and arm movements for greater empathy, and some adaptation of clothing and hairstyle are permitted to reflect brand value, IPSoft is not currently prepared to allow fundamental changes to gender or skin color, or to allow multiple avatars to be used to develop empathy with individual customers. This might need to change as IPSoft becomes more confident of its brand and the market for cognitive agents matures.

Partnering with Consultancies to Develop Horizontal & Vertical IP

At present, Amelia is largely vanilla in flavor and the bulk of implementations are being conducted by IPSoft itself. IPSoft estimates that Amelia has been used in 50 instances, covering ~60% of customer requests with ~90% accuracy and, overall, IPSoft estimates that it takes 6-months to assist an organization to build an Amelia competence in-house, 9-days to go-live, and 6-9 months to scale up from an initial implementation.

Accordingly, it is key to the future of IPSoft that Amelia can develop a wide range of semi-productized horizontal and vertical use cases and that partners can be trained and leveraged to handle the bulk of implementations.

At present, IPSoft estimates that its revenues are 70:30 services:product, with product revenues growing faster than services revenues. While IPSoft is currently carrying out the majority (~60%) of Amelia implementations itself, it is increasingly looking to partner with the major consultancies such as Accenture, Deloittes, PwC, and KPMG to build baseline Amelia products around horizontals and industry-specific processes, for example, working with Deloittes in HR. In addition, IPSoft has partnered with NTT in Japan, with NTT offering a Japanese-language, cloud-based virtual assistant, COTOHA.

IPSoft’s pricing mechanisms consist of:

• A fixed price per PoC development
• Production environments: charge for implementation followed by a price per transaction.

While Amelia is available in both cloud and onsite, IPSoft perceives that the major opportunities for its partners lie in highly integrated implementations behind the client firewall.

In conclusion, IPSoft is now making considerable investments in developing Amelia with the aim of becoming the leading cognitive agent for customer service and the high emphasis on “conversations and empathic responses” differentiates the software from more transactionally-focused cognitive software.

Nonetheless, it is early days for Amelia. The company is beginning to increase its emphasis on third-party partnerships which will be key to scaling adoption of the software. However, these are currently focused around the major consultancies. This is fine while cognitive agents are in the first throes of adoption but downstream IPSoft is likely to need the support of, and partnerships with the major contact center outsourcers who currently control around a third of customer service spend and who are influential in assisting organizations in their digital customer service transformations.