The Boom of AI in Recent Years
In recent years, there’s been a surge in businesses around the world embracing AI (artificial intelligence) at lightning speed. The adoption of AI is driven by factors such as the need to do more with less, the need to turn a tremendous amount of data into actionable insights, and of course – the need to deliver exceptional customer experiences.
This year, more than 80% of companies have adopted AI in some way, with 83% stating that AI takes the top spot in their business strategy. In the UK alone, 68% of large companies, 33% of medium-sized companies, and 15% of small companies have incorporated at least one AI technology.
How AI Thrives in Organizations
While the desire to leverage AI across industries and organizations is strong, implementing it effectively presents an entirely distinct challenge. The maturity of AI efforts within a company depends on several factors, including data fidelity, technology flexibility, corporate culture, and industry regulations.
Data fidelity – this refers to the accuracy, reliability, and consistency of data throughout its lifecycle. Ensuring data fidelity within AI involves rigorous data preprocessing, cleaning, and validation processes to remove errors, inconsistencies, and biases. Data serves as the fuel for AI, embodying the saying “garbage in, garbage out.” This emphasizes the fact that the quality of data you train AI with directly impacts the quality of AI output.
Technology flexibility – Siloed technology can severely hamper the potential of AI for several reasons. Integration challenges, data inconsistency, inefficient processes, and struggle to scale the technology are all issues caused by tech silos. These challenges are made exponentially worse when each technology has its own competing AI.
Corporate culture – Culture eats strategy for lunch, so AI thrives in culture of innovation. A culture that values innovation encourages employees to experiment with new approaches to AI and new solutions to implement AI more effectively.
Industry regulation — Finally, companies in regulated industries are much more cautious in utilizing AI to drive digital transformation. Brands that unlock data in real time, supported by a unified system of action and engagement, and a culture of innovation are thriving.
This includes Standard Chartered, the multinational banking and financial services company that plans to use Sprinklr’s conversational AI capabilities to digitize 70% of conversations to free up live agents for complex transactions that require a human touch, such as mortgage applications and wealth management. With Sprinklr’s enterprise grade governance and compliance framework, the company can take advantage of AI to drive efficiency. As a result, 90% of Standard Chartered first responses to any customer on any channel is within 10 minutes.
AI can elevate business insights
AI is essential in tackling the vast ocean of unstructured and publicly available customer experience data. The size and nature of unstructured data compared to structured data is often referred to as the ocean vs. a swimming pool.
Taming this ocean is impossible without AI. Tackling this requires brands to step back and consider who is talking to them (social listening, call centre transcripts, solicited feedback), who is talking about them (product insights, visual insights, locations insights, reviews and other unsolicited feedback), who is talking about their competition (benchmarking insights) and, finally, who is talking about things they care about (broad social listening). AI helps to derive these insights using advanced language processing, text analytics, and keyword-based queries.
For example, Microsoft, in just one quarter, pulled in nearly 2.2 billion public mentions of the brand and its products through digital listening and used AI to deliver intelligent insights that now informs marketing and development decisions across their entire company.
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AI-driven insights can drive business strategy
While AI stands for Artificial Intelligence, when it comes to driving business strategy it can also stand for “Augmented Information” in marketing. AI is finding its way into the daily life of marketers through AI-assisted asset search, asset tagging, compliance and budget optimization – and Generative AI is expanding this to include campaign strategy suggestions, campaign brief generation, copy suggestion/localization, and creative insights. For example, a leading global beverage company utilizes AI to provide creative suggestions for assets and copy pre-flight, in-flight and post-flight to increase marketing performance and compliance.
AI in customer feedback can mean “Actionable Insights.” You may be used to hearing on the phone the following phrase: “This call can be monitored for quality assurance purposes.” But, the reality is that without AI, less than 1-3% of all calls are actually monitored. AI can do this while at the same time monitoring all other publicly available experience data across all channels.
And finally, AI in customer service can stand for “Automated Interactions.” Bot-based conversational AI helps to manage routine customer queries to free up time for customer service representatives to have higher value conversations. For example, Planet Fitness is using Sprinklr to help it automate interactions and gain insight from customer questions and concerns related to its 2,400+ gym locations.
Another great example is Aramex, a leading logistic company in the Middle East, which now uses Sprinklr’s AI capabilities to handle 95% of customer conversations. As a result, Aramex has reduced calls by 30% and is freeing up agents to cross-sell and up-sell products and services.
Challenges and considerations
With the power, potential and promise of AI looming large, what stands in the way? For some people AI, stands for “Absolutely Incredible” and for others “Awful Idea.” This spectrum underlines the key considerations and challenges of AI.
The first challenge is keeping pace as new providers, models and capabilities show up every month.
Secondly, understanding the changing nature of work as well as the need for new skills required to enhance, maintain and manage AI systems.
Thirdly, the security and privacy implications AI need to be considered, and finally, companies need to address responsible AI providing trust, integrity and transparency.
Overcoming these challenges often means stepping back and asking the age-old question, “what’s the problem we are trying to solve?”
Putting the customer at the centre, defining the specific use case and value, bounding the data required, and refining the model iteratively are all best practices for applying AI to the future of digital transformation.
AI: Act Intentionally
One last alternative meaning of AI: Act Intentionally. Act now. But act with clear intent: understanding the decisions, the use cases, the actions – and the consequences and value to your organization, your employees and your customers.