Artificial Intelligence (AI) can transform customer service however, many AI projects fail at the first hurdle. Henry Jinman at EBI.AI outlines the 5 most common mistakes and how to fix them.
Artificial Intelligence (AI) holds the key to transforming customer service as it allows routine tasks to be delivered faster, at lower cost and on a far larger scale. Chatbots are already commonplace in contact centres while millions of people interact daily with virtual assistants such as Google Home and Alexa. However, for every successful AI project there are many others that fail.
For those organisations who haven’t yet invested in AI, many are experiencing a fear of missing out (fomo). As a result, many are rushing in and AI projects are failing. So, what’s going wrong?
5 reasons why Customer Service AI projects fail
AI technologies are powerful but they can be complex to scope out, build, deploy, and operate. Here are the 5 most common mistakes organisations make:
- Unrealistic expectations: It’s common for users to have inflated expectations of new and emerging technologies. This could be because of marketing over-hype, lack of familiarity with the technology or the simple hope that a new solution is the answer to every problem.
- Addressing the wrong challenges: Organisations often try to fix everything with one project, we call this ‘trying to boil the ocean’. At the other end of the scale, people can spend 18 months writing an AI strategy paper that ultimately delivers nothing. Remember to scope out the issue first and then address the challenge.
- Lack of training data: Many say the more data you have the better. Yes you do need data, lots of it, but it must be relevant data.
- Lack of stakeholder engagement: The people who make or break a project are those responsible for deploying the technology and the leaders of the department paying for it. Remember to involve the budget holders from the very beginning.
- Misunderstood technology: Many AI projects fail for the simple reason that they are not really AI projects. AI technologies for customer contact need to be three things – digital, intelligent and automated.
The secret to successful AI projects
Fixing AI projects starts at the beginning. Don’t rush in and remember to ask these 5 questions:
- How do I measure success? A project is usually deemed to be unsuccessful if it fails to meet a set of pre-defined objectives. For a customer service project these goals could be financial, involving cost savings or revenue targets. Alternatively, they could be operational i.e. seeking to increase efficiency and improve customer satisfaction.
- Where do I start? Most organisations will want to achieve and demonstrate some quick wins but where do they begin? Should they be ambitious and try everything at once or run a mini-pilot to test the waters to find out what works and what doesn’t before going live?
- How do I overcome the fear of unchartered territory? The clue is dare to be ‘different’. If you are normally conservative and play safe, could you change this approach to become bold and experiment even if you fail? It’s a great way to learn and there are even greater ways to share that learning before the all-important go-live.
- How do I test in a real-world environment? Ask yourself how many users and customers should try out the new AI technology? What should be the criteria for selecting them? How do we ensure the new solution can integrate with the production environment, provide the required functionality and deliver a return on investment? Have answers to these questions before you begin.
- How do I ensure a successful roll-out? There are various options to consider including the two most popular methods, known as ‘Incremental Improvement’ and ‘Applying the Learning’. Ask what are the benefits of each and which one is best for my organisation?
Fast-track your way to a new generation of customer interactions by asking the right questions. Then, find out the answers and discover real-world examples of good and bad AI practice by downloading our latest white paper https://ebi.ai/why-ai-fails/
Established by EBI in 2014, Warwick-headquartered EBI.AI is among the most advanced UK labs to explore the mind-boggling potential of Artificial Intelligence for customer communication. It is changing the ways businesses interact with their customers by providing faster and better resolutions to customer queries using conversational AI technology.
The company has applied its collective 18 years’ experience of working with big data, analytics and systems integration to create a range of innovative and natural tools for all businesses in multiple sectors including Transport & Travel, Property, Insurance, Public and Automotive.
EBI was one of the first IBM Watson Ecosystems Partners and EBI.AI’s core platform was originally based on IBM Watson. This has evolved over 5 years and EBI.AI now selects the best AI and cloud services available from IBM, Amazon, Microsoft and others, combined with bespoke AI models to deliver its EBI.AI communication platform.
For more information, please visit www.ebi.ai
