Leveraging data to get ahead? Conversational tech is the next-generation solution to database access.
~10 minute read
We’ve seen it in science fiction for decades: the computer interface that responds when spoken to, sometimes in a pleasant, yet robotic, female voice.
Now, in 2020, Siri and Alexa are regular characters in our everyday lives. The science is no longer fiction, but this conversational technology is still seen as a novelty: virtual assistants that deliver the weather forecast and play your favorite song are relegated to the realm of leisure.
They’re sold as experience enhancers for our everyday lives.
Brands seeking to bring greater personalization at scale are leveraging conversational technology to add this same sense of novel delight to their sales and customer engagement processes. Most of us have used or are familiar with chatbots and virtual assistants when it comes to digital customer service and online marketing interactions.
However, as technology advances further, there are even more powerful applications for conversational systems that behave more… human.
We believe that conversational AI will fundamentally transform human-to-computer interfacing.
Here at Chata, we envision a world where it’s not only possible to interact with computers the same way we interact with other humans, but that this becomes the new norm. We see conversational technology extending far beyond its entertainment value: we believe that conversational AI will fundamentally transform human-to-computer interfacing.
Powerful and innovative conversational technology is the foundation of a new world where access to information is completely democratized.
It’s a step towards a world where anyone can get what they need out of the systems and applications they use, because interfacing with those systems will be as intuitive and as simple as having a conversation––the mode of communication that’s second nature to all humans.
Read more: How to Talk Data with Conversational AI
Conversational Technology is Already Transforming Business
In the business realm, we’ve already seen exponential movement towards the adoption of conversational technologies, and in particular, an increasing demand for and adoption of conversational agents.
Oracle reports that “[This year], 80% of businesses plan to utilize chatbots.” In 2019, Salesforce reported that “58% of customers say emerging technologies such as chatbots and voice assistance have changed their expectations of companies.”
As everyday people come to expect more straightforward interactions with digital spaces like websites and apps, the pressure is on for more complex software to respond to users’ demand for accessibility.
By 2021, 50% of analytical queries will be generated via search, NLP or voice, or will be automatically generated.
More and more of our work has moved onto computers, and our workflows increasingly rely on the use of applications and systems to store, access, share and use the information we need to do our jobs. Access to technology is becoming more widespread than ever.
In light of this, it’s vital that computers and software become increasingly intelligent not only to meet our evolving technological needs, but to simultaneously meet our need for both ease and efficiency, too.
That means computers and software should be built to adapt to human capabilities so that it doesn’t take specialized skills or training to leverage the power of digital innovation.
A democratization of access will inevitably lead to empowerment: more people will be able to get more value out of their software systems. This also means that software providers can open their systems to new user groups who need high-tech solutions, but don’t necessarily have the specifically-skilled labor or resources that may otherwise have been necessary to operate them.
Conversational Technology Moves Data-Driven Culture Forward
An area of profound opportunity? AI-driven business intelligence (BI), analytics, and data access.
Conversational agents made the ever-expanding world of e-commerce more navigable for all kinds of customers; conversational technology built to facilitate the difficult work of database exploration will make it easier for everyone to make the data-driven decisions that are demanded by today’s shifting, competitive market.
Gartner predicts that “By 2021, 50% of analytical queries will be generated via search, NLP or voice, or will be automatically generated.” Furthermore, Gartner’s research shows that “By 2025, a scarcity of data scientists will no longer hinder the adoption of data science and machine learning in organizations.”
These statistics point towards a paradigm shift in the way businesses operate. With so much of our lives happening online, data capturing our actions (from customers’ buying habits, to salesperson success rates, and frontline warehouse activities), is abundant, and it’s expanding every day.
Businesses know that information is a goldmine and they need access to all that data to sell better, buy better, invest better, and grow better.
Gartner also reports that “Information as an asset is still in the ‘early adoption’ phase, which makes it a competitive differentiator for leading organizations as they focus on digital transformation,” and that “By 2022, 90% of corporate strategies will explicitly mention information as a critical enterprise asset and analytics as an essential competency.”
Mckinsey Global Institute supports the observation that businesses are increasingly using data to improve, reporting that data-driven organizations are 23 times more likely to acquire customers. They’re also six times as likely to retain those customers and 19 times more likely to be profitable.
Conversational Tech is at the Forefront of Digital Transformation Initiatives
We’re in the midst of massive digital transformation across industries.
To be totally data-driven, companies are catching on to the fact that it’s not just high-level executives who need access to information to make critical choices about the business. Employees at all levels of the enterprise need to be able to use the data contained in the systems they use every day to make strategic and informed moves towards their goals.
To offer impactful solutions in this arena, conversational technology needs to be developed specifically for database access.
To serve every employee in every department, databases, and the tools that help humans draw meaning out of data (like BI and reporting and analytics software), need to be easy to use. If not, the solutions are underused at best, and impossible to scale at worst.
To offer impactful solutions in this arena, conversational technology needs to be developed specifically for database access. That’s where innovation in conversational AI enters to support the tasks that typically fall, and even end up restricted to, a software engineer, data analyst, or an in-house BI specialist.
This trend towards the empowerment and enablement of the everyday business person – the citizen data scientist – cannot be understated. By 2021, automation of data science tasks will enable citizen data scientists to produce a higher volume of advanced analysis, than specialized data scientists (Gartner).
Improved AI will Take Current Technology to the Next Level
Conversational AI technologies encompass machine learning techniques such as natural language processing (NLP) and natural language understanding (NLU). Currently, many chatbots leverage some amount of AI technology, like intent classification, which requires a system to understand human language and match it to a pre-determined action or suggestion. But when it comes to applying conversational AI to make the task of data access and analysis easier for all, intent-based systems simply fall short.
The technology needs to be more intelligent, more intuitive, and more powerful.
The conversational AI that will have the highest impact on data experiences needs to be able to understand human language (natural language) and dynamically translate natural language to database query language––the language used to get information into and out of database systems––to act as a knowledgeable concierge and a fluent translator for users seeking answers in their data.
Furthermore, this new wave of conversational AI technology needs to offer a holistic user experience that puts exceptional communication first and ensures that understanding and translation is seamless, so users at any level of technical or data aptitude can get exactly what they need, just by asking for it.
Conversational AI built for database access will fundamentally transform the way people access and interact with their data.
To achieve widespread adoption of data science and machine learning initiatives across organizations, conversational AI systems must not only advance to meet users where they are at, they must also be easy to introduce and maintain at scale for the businesses who implement them.
Conversational AI built for database access will fundamentally transform the way people access and interact with their data. As more businesses move towards a data-driven model and culture, conversational AI technologies will be in increasingly high demand from companies looking to arm their employees with the valuable information stored in their ever-growing databases.
Doing Our Part to Build the Conversational Experiences of Tomorrow
We believe that data is at the heart of the successful businesses of tomorrow. Thanks to innovations in conversational AI and improved conversational interfaces, we see a future where everyone can access important information more easily and find insights in their data more intuitively.
As a company, we know how critical data access is to making decisions for our own business, which is why we’ve chosen to focus on creating conversational AI solutions specifically for this domain.
As innovators, our part to play lies in both the development and betterment of conversational AI technologies that empower others to access and leverage data on their own roads to success.