By Evan Brown


Many challenges await start-up companies within the already-busy AI space. Today, it seems as if every new tech company is branding as ‘an AI company’; indeed, while VCs invested barely $415 million in AI ventures in 2012, AI spending is forecasted to grow to $37bn by 2025, according to research by Tractica. Accenture estimate that economic growth will be doubled with a productivity boost of about 4%.

The thing is, AI delivers digital consistency and puts brand insecurities to rest. A survey by The Economist revealed that 75% of the total 203 magnates are planning to incorporate AI into their business within the upcoming 3 years. It is also obvious that AI will lend companies a competitive edge in the market by giving them the ability to offer gilt-edged customer service functions. The challenge remains, however, when everyone and their grandmother is rebranding for the age of AI: how can we stand out?

In this article, we’ll take a look at some of the attempts being made to differentiate AI products and solutions, as well as the effects of AI on technology branding. After that, we’ll examine how companies are making use of the tools themselves to gain an edge in the market.

AI in Branding: The State of Play

According to the Harvard Business Review, many companies are already looking to plan, organize, and implement AI technology across an array of business practices. These practices include management of non-customer external relations (28%), marketing and sales (35%), and customer services (39%), among others.

When it comes to employing AI across these practices, enterprises are turning en masse to chatbots or virtual assistants. Microsoft’s Cortana, Apple’s Siri, and Amazon’s Alexa not only act as new user interfaces and a means of automating certain aspects of customer care, but also serve as individual personalities which reinforce those companies’ brands.

Take the example of IPsoft’s Amelia. Amelia is a humanoid AI desk agent that, using algorithmic data from millions of databases, is able to automate countless business processes and serve several functions across the enterprise. Currently, Amelia appears virtually onscreen, but in the near future, holographic technology might make it possible to place a life-size Amelia at our service.


amelia cover photo

Related: End-To-End Automation In Large Enterprises Augments Human Talent


Another notable mention here is Cleo, billed as the AI friend who takes care of your money. This AI-driven Messenger chatbot combines natural language processing and fintech to organize users’ finances using intelligent insights and a simplified interface. In order to give Cleo a more personal human look and feel, the developers set out to give the AI an ‘overfamiliar’ personality. Thanks to this, a recent survey revealed that 77% of about 1000 Cleo users stopped using banking apps to manage their finances within 3 months.

Giving chatbots a human name – whether it’s Amelia or Cleo – is not only suited to the tasks performed by these AI assistants. The tendency of AI to cope up with human behavior and learning system sets the foundation for this technology being named after humans. Moreover, the companies behind these AI projects use these machine leaning personalities to build a platform that represents their ‘human aspect’ uniquely.

The effects of AI on branding

The applications of AI technologies within branding itself are numerous. The McKinsey Global Institute (MGI) published a recent report, Artificial Intelligence: The Next Digital Frontier?, discussing how AI is deployed by several companies and how much is invested in this evolving field. Of course, the way AI will eventually transform a brand depends on how the brand in question decides to use it.

Brand fluidity

The trend of fluid or liquid branding is emerging as businesses opt for new communication channels driven by AI technology. The liquidity or fluidity of a brand is maintained mostly through a personified tone and conversational interface for which most of the AI chatbots are programmed. AI keeps the brand adaptable and versatile, enabling it to keep evolving with time. It comes as no surprise that investment from tech giants aggregated to $18-$27 billion alone in AI technology in 2016, while external funding amounted up to $8-$12 billion.



Greater consumer insights

A brand’s power is its consumers. AI technologies provide the ability to learn and develop intelligent insights from exponential sets of data – be they structured or unstructured. The machine learning aspect of AI digs deep into the myriad of data sets and retrieves information regarding consumer behavior, which enables brands to discover unanswered customer requirements. Moreover, brands can form the right structural framework by segmenting the information from data sets to define the brand approach.

A notable example is Nestle’s use of machine-learning forecast system that employs algorithms and hierarchical data to predict future sales. Nestle uses supply chain forecasting to improve global predictions, which enhanced its sales forecast by 9% in Brazil.

More creative, targeted approaches

As AI’s deep learning ability has led to a macroevolution in speech recognition, image procession, and vocal translation, indispensable creative opportunities await brands. When brands want to gain recognition of targeted audience insights, they can rely on machine learning to cater and align an array of relative consumer data from massive unstructured data sets. This way, they can use creative structured data to design the type of communication and elements appealing to their prospects.

For example, McCann Japan, a Japan-based ad agency, introduced an AI creative director in competition with a human to create an ad for Mondelez brand Clorets Mint Tab. The company accessed the database of award-winning ads in order to train the AI creative director to help it recognize the success factor. Though the human competitor won, the future for AI’s ability to learn and create ads indicates a pragmatic future, where humans create algorithms and machine learning structures them.

Machine learning isn’t just confined to recognizing consumer patterns and behaviors or analyzing algorithms. It also has the ability to align the creative interests of a brand with its respective influencer and create opportunities. Using AI to access unorganized data from social media sites, brands can recognize potential influencers as well as the key elements and content types driving their audience, creating brand awareness and advocacy opportunities.

Brand challenges lie ahead – but so does opportunity

As expectations keep growing, brands may confront several challenges as a result of AI implementation. These challenges might be technical, regulatory, and commercial in nature. However, AI will become a key driver of customer experience and engagement. The time is approaching when AI will take control of consumer choices, influence their decisions, and will make tasks easier. All these functions of AI depend entirely upon the data and the decision-making ability of the system.

Moreover, all the classes and subsets of the artificial intelligence will be connected within a structured framework, introducing new areas of brand approaches. With AI, brands can gain a deeper insight into the consumer behavioral patterns exhibited in the unstructured data sets. If companies approach AI with the determination to innovate and reincarnate their brand, not only can their business flourish today, but also remain sustainable and versatile in the years to come.


EB

 

Evan Brown is a Digital Marketing pro who’s been proactively engaged with the cyberspace since 2008, focusing on design services, user interface planning, and branding with a never-ending list. He now leads content marketing efforts at DesignMantic