Slalom Ventures: Are You Ready to Talk to Your AI?
The future of linguistic AI is here. Learn how to take advantage for your organization.
On May 11, 1997, the world watched in awe as the world chess champion was narrowly defeated by a computer known as IBM Deep Blue. Two wins for IBM, one for the champion, and three draws. The match received massive media coverage because who doesn’t love the age-old tale of man versus the machine?
“Some people are apprehensive about what the future can bring, but it’s important to remember that a computer is a tool. The fact that a computer won is not a bad thing.” — Feng Hsu
Deep Blue’s AI was an instance of what the future of computing could look like, yet it was a far cry from the average technology of the late 1990s. While Deep Blue showed us how impressive these algorithmic capabilities had become, it was not clear how this specialized intelligence would really affect our daily lives. Fast-forward to 2023 and AI technology, particularly conversational-based AI, is on the precipice of being integrated throughout all aspects of commerce and life.
Why?
Solving problems through language is ingrained in our society, and our technology should reflect that.
Venture capital investors are focused on the coming age of AI: over $1.7 billion has been invested into generative AI solutions by venture capital firms in the last five years. New solutions, especially from startups, are bridging the gaps for solutions in industries that were untapped.
What is conversational AI?
Conversational AI is a set of technologies that allow an application to interact with humans via voice or text. It leverages aspects of machine learning (ML) and natural language processing (NLP) to better understand interactions and the nuances of linguistics. Training AI in linguistics involves not only recognizing individual words but also understanding how they relate to each other in a sentence and the broader context in which words are used. This requires advanced algorithms and models that can capture the intricacies of language use. One aspect of NLP is automated speech recognition (ASR), which refers to the technology used to transcribe spoken language into text. ASR has seen recent improvements in lower error rates across different pitches and acoustic characteristics.
How does technology change?
Technology moves through essential steps as it becomes ingrained in everyday life. Computer keyboards mimic the typewriter to help original users’ comfort levels. Users are uncomfortable with change, but once technology shows positive social movement, we look back and wonder how we ever lived without it. Conversational AI is moving into an era of adoption through new technology that is designed for the average user.
Siri and Alexa have already become the stepping stones for daily conversational AI use. Their popularity was unprecedented in the early 2010s even though the experience was clunky compared to the newest versions that know 20x more facts. The conversational AI technology has continued to skyrocket in popularity with ChatGPT success in user acquisition, engagement, and plans for corporate integrations. Zillow has just rolled out their own conversational AI for customers to ask real estate questions.
Why is AI important?
A vast majority (81%) of executives said that artificial intelligence would either be critically important or very important to their companies in 2022. But why? AI can ultimately change the daily work streams of workers and increase their access to information. Workers will spend less time performing repetitive tasks, capturing the nuances from conversations, and locating important answers without searching tediously through documents.
Linguistic-based AI will unlock areas of business that go beyond freeing up workers’ time; it will support accessibility, reduce the strain on job markets, and improve user experiences.
Major conversational AI adoption challenge: Noise
The use cases for conversational AI can feel vague to the average company, but proper planning can create major paradigm shifts within all organizations. In a report on the State of Connected Operations, IoT company Samsara found that organizational leaders are predicting that by 2025, 55% of their employees in the field will rely completely on digital workflows to perform day-to-day tasks. AI use cases are still overcoming issues such as noise, bias, and more, yet the technology being created by startups is solving them in real time.
Envision a doctor using AI to enter diagnostic information in an ER to keep their hands free.
The ER is a noisy environment, packed with patients, doctors, and equipment. The current technology struggles to separate the background noise and other voices in the room to hear only the doctor’s voice. Current AI technology struggles with noise, which continues to impede its daily use at hospitals, factories, and similar environments.
At Slalom, we have had the opportunity to work alongside Yobe, a technology engine that allows AI to recognize voices of interest in loud spaces. Yobe leveraged our network and insights during our Slalom Ventures: AI for Good accelerator. The AI uses biometric data to recognize and track a specific voice of interest and ignore background noise, similar to how our own ears filter noise. It works across different environments, like how you can pay attention to one voice while in a group of people talking. Yobe’s technology also employs the use of biometric data that can be leveraged in the future by industries where sensitive information is being communicated to AI and only certain personnel should be recognized to ensure safety.
“CAFE Yobe’s edge-based software extracts clean, high-quality, and machine-recognizable voice data, including sophisticated linguistic patterns and biological markets.” — Ken Sutton, founder of Yobe
Yobe’s solution, unlike any other on the market, allows for accuracy and creating voice profiles to support a solution that is dynamic. The technology that Yobe has created would allow the doctor to use AI to enter diagnostic information in an ER setting with ease, and the AI would, over time, be able to improve its understanding of patterns appearing in the ER, the doctor’s habits, and more. This type of innovation is crucial in industries that are facing staffing shortages while needing to focus on high levels of care at lower costs. The biometric aspect of voice recognition will also be crucial in the future for security purposes.
What is coming next?
Current AI technology is growing at an unprecedented rate. Solutions and new companies pop up almost daily. User interactions are growing at a similar pace since the pandemic, where interaction with conversational AI is up 250% in multiple industries. The near future holds the promise of further AI accessibility, such as people becoming trained in prompt engineering and similar processes. There will also be a continued growth of standardization over the technology baseline for the major technology going to market. As Yobe and other startups have shown us, Siri and Alexa are great, but they are not up to the standards that most companies need to meet the linguistic complexity or even the noise level of their spaces.
Why will companies do this?
To some, the use case of conversational AI feels vague and closer to technology only found in sci-fi movies. The possible use cases are expanding and increasingly accessible, but technology integration will remain a time-consuming process at scale. Luckily, this technology will increase productivity and improve customer experiences, which in turn should show positive bottom-line growth.
The more a company creates thoughtful use cases and integration planning, the more likely the benefits will be recognized almost instantly. Some studies predict that by 2027, AI-powered innovation teams will deliver up to 75% more successful projects than traditional human teams, leading to accelerated value generation from applied innovations. AI will continue to gain intelligence, but more importantly, it enables teams to automate, create efficiencies, and focus on their strengths. Value generation will be found by creating time-saving solutions and AI that is predictive of consumer needs, which allows for interactions that the average consumer will benefit from. Conversational AI has the potential to transform traditional methods with broader applications that are unlocked through linguistics and similar AI technologies.
How can Slalom help?
Slalom is at the forefront of humanizing technology and continues to understand the incoming trends of business. We’re experts in fostering data-driven companies and support them in their success with AI. Our AI for All initiative is just one example.
Learn more about Slalom Ventures — a team within Slalom Strategy that incubates and connects startups to Slalom’s global network of consultants and clients with the aim of solving the world’s biggest problems and highlighting innovative solutions.
Slalom is a global consulting firm that helps people and organizations dream bigger, move faster, and build better tomorrows for all. Learn more and reach out today.
