Top 5 Voice AI Implementation Challenges and How to Overcome Them

Ernest Lee

Marketing and Communications, AI Rudder

AI and automation have become widely popular in recent years, with much of the uptick happening at the height of the Covid-19 global pandemic. Chatbots using conversational AI are now commonplace in many brands’ social channels and there is no doubt that Voice AI will be one of the next technology trends that will define the next decade and the 4th industrial revolution.

By 2022, voice-activated shopping is estimated to have a value of US$40 billion in the United States. And as of 2020, 62 per cent of smart speaker owners have bought items through voice commerce. More interestingly, 85 per cent of surveyed shoppers said they have occasionally taken their voice assistant’s purchase recommendations, instead of buying from the brand they initially intended. While these statistics reflect consumer preferences in the US, it still shows how powerful Voice AI can be in the years to come.

The Voice of the Future

Widespread adoption of Voice AI will largely hinge on its integration with mobile applications. Many companies are integrating voice technology into customer touchpoints, recognising that a voice interface eases app adoption for new users. While the technology is currently nice-to-have, Voice AI may soon become a standard offering in any customer-facing application.

Voice search is also gaining momentum, through the increasing use of smart speakers. While Amazon Echo, Amazon Dot and Google Nest speakers dominate the voice search arena today, experts believe it will soon be taken over by mobile voice search. With that growth comes lots of potential earnings. According to Juniper Research, ad revenue from voice search can reach US$19 billion by 2022.

Advances in voice technology will enable AI to distinguish between voices and offer individualised experiences. Voice recognition can be the gateway to customised features and curated offers. However, this might not come for a while, as voice technology still struggles to understand some voice types and accents, such as that of children. Fast speech at more than 200 words per minute is also difficult for AI to catch and interpret.

Another hurdle that will need to be overcome is filtering out background noise. Without noise cancellation, any voice interface will have a hard time understanding commands, no matter how sophisticated the AI is. Thankfully, a lot of software has been developed to counter this obstacle and the technology will only get better with time.

Implementing Voice AI technology

If you’re looking to adopt Voice AI for your enterprise, there are a couple of things to consider and possibly make adjustments for. Here’s a list of common roadblocks that can be overcome with thoughtful planning and making the right choices.

Legacy IT Infrastructure  

Often, a company’s existing IT architecture is not able to meet the requirements for AI technology. This is especially the case for enterprises that still rely on on-premise infrastructure, whose loads and capacities are fixed and often fully utilised. Even if your infrastructure has spare capacity, relying on existing technology may mean losing out on the full benefit of data analytics that yields valuable insights to your business.

Choosing to increase on-prem computing power or shifting to the cloud will take time and resources, and slow down Voice AI adoption. A viable alternative is to use AI Rudder’s plug-and-play Voice AI system in your existing infrastructure. AI Rudder’s platform runs on the cloud, and can seamlessly integrate and scale with your customer base whenever and wherever you want it.

Data management

As many data scientists know, AI is only as powerful as the dataset that feeds it. While unstructured data, like audio recordings, holds immense value for a business, many organisations are not able to glean valuable insights from their datasets. This is because unstructured data can’t be analysed with conventional systems.

With Voice AI, unstructured data can be broken down, processed, and stored as easier-to-understand analytical data. This makes it easier for businesses to draw insights from data and make meaningful, data-driven decisions to supercharge their customer experience. Identifying and unlocking the right kinds of data will help make AI adoption extremely powerful in your organisation.

Data security and storage

In today’s data-driven world, data security should be one of the top priorities in any tech implementation. Where you store data and how you keep it secure from breaches are key decisions that need to be made prior to AI adoption.

Certificates such as SoC and ISO are the bare minimum requirements for data safety. Be sure to ask providers for IT or data-related audit reports for your compliance team to inspect and make sure that things are in place.

Customer privacy concerns

Consumers today know that companies keep their digital data stored for analytics. Before launching into any tech adoption that involves big data, make sure you have the right protocols in place for customer consent, data collection, and privacy.

For example, always have opt-in and opt-out clauses for users to give your customers a sense of control over what information they share. Personally identifiable information such as voiceprints should be treated with the utmost respect to privacy. Incorporating “Privacy by Design” will help give consumers peace of mind regarding their data.

System management

Once your AI strategy is in place and your tools are up and running, you may find yourself facing a different set of challenges. Scaling and growing your AI tools bring other pain points with it. One such issue is the need for in-house experts to manage your AI program.

However, not every organization can afford to hire a machine learning expert, and that’s where AI Rudder’s enterprise-ready Voice AI comes in. The technology seamlessly integrates with existing IT infrastructures, removing the need for businesses to hire a team to support, operate and maintain the system.

Furthermore, AI Rudder’s SaaS model deploys upgrades automatically, foregoing the need to do manual updates. Deploying updates on the cloud also reduces downtime, ensuring round-the-clock productivity.

Gearing up for Industry 4.0

As AI technology continues to progress, automation through voice technology will soon become a part of everyday life. Companies that embrace Voice AI will find themselves ahead of the curve and reap the most rewards from early adoption. Starting your AI strategy today – even a small step – can set you up for immense future success. Plug-and-play solutions are a great way to dip your feet into the water and prepare for the wave of Voice AI adoption coming to our shores.

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