Afiniti has been recognized as a Bronze winner in the 18th annual Stevie® Awards for Sales & Customer Service thanks to the great partnership we have with LivePerson.

Sam Logan, chief legal officer of Afiniti, provides an inside look to AI-powered customer service and predicts how emerging technology will change the way brands and buyers interact.

Additionally, our Chief Partnership Officer, Ben Evans​ took part in a panel session with people from Avaya, Genesys and Cisco and spoke to a packed room about the future in his “Contact Centres / CX 2027: What Will Drive the Market” session.

Ben emphasised the importance of clear objectives and measurable business outcomes, stating, ”Companies need to think beyond cost reduction when embracing these new technologies. At Afiniti, we look at how our technology can improve customer retention and lifetime value.”

At Booth 1311, our team engaged with industry leaders, potential leads, partners, analysts, and media representatives, showcasing the potential of our solution. Check out them at our booth with their cool Afiniti t-shirts!

The use of AI in consumer-facing businesses is on the rise — as is the concern for how best to govern the technology over the long-term. Pressure to better govern AI is only growing with the Biden administration’s recent executive order that mandated new measurement protocols for the development and use of advanced AI systems.

AI providers and regulators today are highly focused on explainability as a pillar of AI governance, enabling those affected by AI systems to best understand and challenge those systems’ outcomes, including bias.

While explaining AI is practical for simpler algorithms, like those used to approve car loans, more recent AI technology uses complex algorithms that can be extremely complicated to explain but still provide powerful benefits.

OpenAI’s GPT-4 is trained on massive amounts of data, with billions of parameters, and can produce human-like conversations that are revolutionizing entire industries. Similarly, Google Deepmind’s cancer screening models use deep learning methods to build accurate disease detection that can save lives.

These complex models can make it nearly impossible to trace where a decision was made, but it may not even be meaningful to do so. The question we must ask ourselves is: Should we deprive the world of these technologies that are only partially explainable, when we can ensure they bring benefit while limiting harm?

Even US lawmakers who seek to regulate AI are quickly understanding the challenges around explainability, revealing the need for a different approach to AI governance for this complex technology — one more focused on outcomes, rather than solely on explainability.

Dealing with uncertainty around novel technology isn’t new

The medical science community has long recognized that to avoid harm when developing new therapies, one must first identify what the potential harm might be. To assess the risk of this harm and reduce uncertainty, the randomized controlled trial was developed.

In a randomized controlled trial, also known as a clinical trial, participants are assigned to treatment and control groups. The treatment group is exposed to the medical intervention and the control is not, and the outcomes in both cohorts are observed.

By comparing the two demographically comparable cohorts, causality can be identified — meaning the observed impact is a result of a specific treatment.

Historically, medical researchers have relied on a stable testing design to determine a therapy’s long-term safety and efficacy. But in the world of AI, where the system is continuously learning, new benefits and risks can emerge every time the algorithms are retrained and deployed.

The classical randomized control study may not be fit for purpose to assess AI risks. But there could be utility in a similar framework, like A/B testing, that can measure an AI system’s outcomes in perpetuity.

How A/B testing can help determine AI safety

Over the last 15 years, A/B testing has been used extensively in product development, where groups of users are treated differentially to measure the impacts of certain product or experiential features. This can include identifying which buttons are more clickable on a web page or mobile app, and when to time a marketing email.

The former head of experimentation at Bing, Ronny Kohavi, introduced the concept of online continuous experimentation. In this testing framework, Bing users were randomly and continuously allocated to either the current version of the site (the control) or the new version (the treatment).

These groups were constantly monitored, then assessed on several metrics based on overall impact. Randomizing users ensures that the observed differences in the outcomes between treatment and control groups are due to the interventional treatment and not something else — such as time of day, differences in the demographics of the user, or some other treatment on the website.

This framework allowed technology companies like Bing — and later Uber, Airbnb and many others — to make iterative changes to their products and user experience and understand the benefit of these changes on key business metrics. Importantly, they built infrastructure to do this at scale, with these businesses now managing potentially thousands of experiments concurrently.

The result is that many companies now have a system to iteratively test changes to a technology against a control or a benchmark: One that can be adapted to measure not just business benefits like clickthrough, sales and revenue, but also causally identify harms like disparate impact and discrimination.

What effective measurement of AI safety looks like

A large bank, for instance, might be concerned that their new pricing algorithm for personal lending products is unfair in its treatment of women. While the model does not use protected attributes like gender explicitly, the business is concerned that proxies for gender may have been used when training the data, and so it sets up an experiment.

Those in the treatment group are priced with this new algorithm. For a control group of customers, lending decisions were made using a benchmarked model that had been used for the last 20 years.

Assuming the demographic attributes like gender are known, distributed equally and of sufficient volume between the treatment and control, the disparate impact between men and women (if there is one) can be measured and therefore answer whether the AI system is fair in its treatment of women.

The exposure of AI to human subjects can also occur more slowly for a controlled rollout of new product features, where the feature is gradually released to a larger proportion of the user base.

Alternatively, the treatment can be limited to a smaller, less risky population first. For instance, Microsoft uses red teaming, where a group of employees interact with the AI system in an adversarial way to test its most significant harms before releasing it to the general population.

Measuring AI safety ensures accountability

Where explainability can be subjective and poorly understood in many cases, evaluating an AI system in terms of its outputs on different populations provides a quantitative and tested framework for determining whether an AI algorithm is actually harmful.

Critically, it establishes accountability of the AI system, where an AI provider can be responsible for the system’s proper functioning and alignment with ethical principles. In increasingly complex environments where users are being treated by many AI systems, continuous measurement using a control group can determine which AI treatment caused the harm and hold that treatment accountable.

While explainability remains a heightened focus for AI providers and regulators across industries, the techniques first used in healthcare and later adopted in tech to deal with uncertainty can help achieve what is a universal goal — that AI is working as intended and, most importantly, is safe.

About Dr. Caroline O’Brien
Caroline O’Brien is chief data officer and head of product at Afiniti, a customer experience AI company.

About Professor Elazer R. Edelman
Elazer R. Edelman is the Edward J. Poitras professor in medical engineering and science at MIT, professor of medicine at Harvard Medical School and senior attending physician in the coronary care unit at the Brigham and Women’s Hospital in Boston.

Originally published in VentureBeat on January 7, 2024.

WASHINGTON – January 5, 2024 – Afiniti, a leading customer experience (CX) artificial intelligence (AI) applications and infrastructure provider, announces the appointment of Mike Myshrall as Chief Financial Officer.

“I am delighted that Mike is joining our leadership team as CFO,” said Hassan Afzal, CEO of Afiniti. “His experience with high-growth technology companies will be a huge asset as we continue to expand our CX AI optimization services and infrastructure offering for enterprises around the world.”

Mr. Myshrall is a seasoned CFO with a strong background in both the public and private equity sectors. He is a hands-on leader who specializes in strategic growth and possesses extensive knowledge of Software-as-a-Service (SaaS) and annual recurring revenue (ARR) business models and metrics.

Mr. Myshrall has a proven track record of driving financial success in dynamic and fast-paced environments, and extensive experience in leading global teams.

“I am thrilled to be joining Afiniti, an extremely innovative AI technology company with impressive talent,” said Mr. Myshrall. “As CFO, I am excited to partner with Hassan and the leadership team to help execute on Afiniti’s high-growth strategic plan, as well as to serve its employees, investors and enterprise customers. Afiniti leverages all of the positions I have held and experiences I have had throughout my professional career.”

Prior to joining Afiniti, Mr. Myshrall was CFO at PrimePay, a leading SaaS technology and services provider in the US. Before PrimePay, he spent ten years at Cyren, a publicly-traded global cybersecurity company with Finance and Accounting teams in the US, Europe and the Middle East. Mr. Myshrall has also worked as a management consultant and investment banker in the telecom and software sectors and holds an MBA from Harvard University and a degree in Electrical Engineering from the University of New Brunswick.

Media Contact

media@afiniti.com

About Afiniti

Afiniti is a leading provider of customer experience (CX) artificial intelligence (AI). Our CX AI optimization services and infrastructure deliver measurably better business outcomes for some of the largest enterprises in the world. Our technology is used globally in the healthcare, telecommunications, hospitality, insurance, and banking industries, and across multiple customer experience channels. To learn more, visit www.afiniti.com.

Afiniti President, Tom Inskip, moderated a panel at COP28 with the Sustainable Markets Initiative on the role of digital technology in accelerating sustainability, featuring Tony Bates, the CEO of Genesys, Kate Kallot, the CEO of Amini AI, Natasha Franck, the CEO of EON, and Greg Jackson, the CEO of Octopus Energy.

Tom and the panellists agreed that decarbonizing technology’s own footprint is essential not only to achieve the global sustainability objectives set by the United Nations, but also to build confidence in technology and AI as drivers of sustainability. Digital technology and AI have a crucial role to play in helping other sectors minimize their carbon footprint, through innovation, data and AI that lead to sustainable action and behaviors all through the value chain of any product or service.

“At Afiniti, we are committed to taking the necessary steps to ensure that sustainability is at the heart of everything we do,” said Inskip. “As a leading technology company, we need to encourage and support sustainability, and help spread knowledge on what we can do as an industry to achieve sustainable outcomes.”

WASHINGTON – September 27, 2023 – Afiniti, the leading customer experience (CX) artificial intelligence (AI) application and cloud infrastructure provider, announces that Executive Vice President and Chief Commercial Officer, Tom Inskip, has been promoted to President of Afiniti.

In this new position, Mr. Inskip is charged with the broad responsibilities of leading all of the customer and partner-facing activities for the company. The role is chartered with delivering on all of the company’s growth and marketing opportunities, as well as presenting a unified, best-in-class customer experience to Afiniti customers and partners worldwide.

“Tom has played an instrumental role in Afiniti’s growth. I’ve had the pleasure to work alongside Tom for over a decade, and consider him an extraordinary growth leader, and business development and marketing talent,” said Hassan Afzal, CEO of Afiniti. “I am confident that his appointment positions us to fulfil our ambition to become the undisputed global leader in CX AI.”

“It’s an honor to work with Hassan and our talented colleagues at Afiniti. We share a passion for making our customers and partners successful, and are excited to play an instrumental role in ushering in a new era of CX AI,” said Mr. Inskip. “More now than ever, our customers are turning to AI to optimize for better outcomes at every turn – this is our expertise.”

Since 2013, Mr. Inskip has been responsible for revenue, helping the company achieve over 40% annual growth across a global customer base, while playing a key role in evolving our product portfolio beyond our AI Optimization solutions (AI Pairing, AI Offers, and AI Commissions) to include our AI Cloud Infrastructure product suite Afiniti Inside^TM, which incorporates AIRO^TM, our new “self-serve” offering.

Media Contact

media@afiniti.com

About Afiniti

Afiniti is a leading provider of customer experience (CX) artificial intelligence (AI). Our CX AI optimization services and infrastructure deliver measurably better business outcomes for some of the largest enterprises in the world. Our technology is used globally in the healthcare, telecommunications, hospitality, insurance, and banking industries, and across multiple customer experience channels. To learn more, visit www.afiniti.com.

Afiniti President Thomas Inskip moderated a fireside chat hosted by Mike Fries, Chief Executive Officer and Vice Chairman of Liberty Global, and Balan Nair, Chief Executive Officer of Liberty Latin America, at Afiniti’s Senior Leadership offsite in October.

Mike shared insights about Liberty Global’s 30-year growth history, the group’s international expansion and the synergies between its different consumer brands that include Virgin Media O2 in the UK, Telenet in Belgium, Sunrise in Switzerland and Virgin Media in Ireland.

Mike, Balan and Tom had an engaging discussion about the future of the global telco industry, and about how artificial intelligence will revolutionize the telecom and cable space. Mike, Balan and Tom spoke about Liberty Global’s and Afiniti’s commitment to innovation and their investments in cutting-edge technology through new products, services and partnerships. Mike and Tom agreed that all artificial intelligence strategies should place the customer at the center and aim to drive incremental growth alongside traditional marketing and sales methods.

We look forward to continuing our strong partnership with Liberty Global!

AI is driving one of the biggest business transformations in history, where companies are moving fast to figure out how to use the technology to deliver more for customers.

The acceleration of AI has also sparked conversations about the effect it’ll have on employment – in particular, whether smart technology is undermining the value of human labour.

Across many industries, this fear is playing out in both the customer and employee experience, with a heavy focus on how generative AI will disrupt traditional ways of working, and how people interact with companies.

This disruption is often painted in stark terms, where employment opportunities will decline as machines move to the centre stage.

But companies that harness this technology to connect and empower people, rather than replace them, will find success with their customers, higher revenue and happier employees.

What the customer experience typically looks like

The contact centre at, say, a large health insurance company is the tip of the spear for the customer experience. The phones are ringing every second with customers wanting to know any number of details of their insurance package. What does it include? How quickly can payouts be made? What paperwork is involved?

Each customer is different: one is a first-time caller anxious to be told that they will receive full support; another knows the insurance process well and simply wants clarity on a few details; yet another is frustrated at having to go through the process yet again.

On the customer service side, contact centre agents are often grouped by skill set, as determined by the organisation’s business goals. Customers are typically routed to the first available agent within a group based on what they’re calling about, which leaves the opportunity of an optimal connection to chance and money on the table.

Improving, not undermining, the human element of CX

There are two false assumptions about the contact centre. The first is that agents are all alike; the second is that AI can now do the same jobs that humans have typically done – or better.

“While generative AI chatbots are great at simple interactions, such as helping a customer get updates on their account, they can’t do everything,” said Syed Adeel Ahmed, VP of AI R&D at Afiniti.

“In higher stakes interactions, like when a customer is filing a claim for a health procedure, the empathy only another person can provide makes a huge difference and can’t be replicated by a chatbot.”

Afiniti’s CX AI technology is designed to enhance, not undermine, the human element of the customer experience.

Just as each customer has a unique set of needs, each agent has their own set of skills and experience. The key challenge is designing an effective customer experience that harnesses this diversity to successfully match the right agent with the right customer.

Afiniti’s technology kicks into gear the second a customer makes contact with a contact centre. It’s at that first point of connection where the experience optimisation begins.

“Instead of routing the customer to the first available agent, as is often the case, companies use Afiniti’s AI to pair customers with agents based on historical patterns of data – such as how an agent has handled similar interactions and why a customer has contacted the company in the past,” said Ahmed. “This puts the agent in a position to deliver on critical metrics, like closing gaps in care, so the customer leaves the interaction satisfied.”

The success of any AI tool rests on how dynamic it can be, and how it can respond to challenging scenarios. Afiniti’s AI engine trains continuously, and on any given day may take into consideration hundreds of variables, such as product launches and agent turnover, to construct optimal models for connecting customers and agents.

The result? A better customer and agent experience and measurable increases in revenue.

Afiniti’s innovations support large enterprises – in insurance, telco, finance and hospitality – that are dealing with thousands to hundreds of thousands of calls each day.

Ensuring fairness with AI

Another concern about AI is the potential for bias to emerge and affect its decision-making processes. Afiniti has designed its tool so that it is constantly monitoring signs of bias, and quickly correcting them.

“Measurability is essential when implementing any AI technology to ensure it is both safe and effective,” said Ahmed.

“At Afiniti we turn our technology on and off throughout the day to create a benchmark. This allows us to continuously track whether bias or other unwanted effects are emerging when our AI is active so we can quickly mitigate them. We use this same capability to precisely measure the value our models are delivering against important business metrics.”

Afiniti has also addressed another unwanted effect that many contact centres face – uneven utilisation of agents. Often, contact centre agents considered high performers are routed to more customers than they can handle, while perceived lower performers aren’t given enough customer interactions to deliver on their KPIs.

Afiniti applies its technology fairly, harnessing the unique abilities of each agent across the contact centre at all times to ensure a consistent distribution and utilisation of agents – meaning no one slips to the bottom of the pile and no one gets burned out.

The need for human connection isn’t going anywhere

AI is exploding, and as Afiniti shows, the human connection complemented with advanced AI will be the foundation of the future customer experience.

After all, customers will always seek the reassurance that comes with human connection – the knowledge that you are being listened to, and that your concerns are being addressed.

AI can facilitate a better experience when it works with, not apart from, humans.

Originally published in Business Reporter on October 4, 2023.