Businesses across industries are re-evaluating their application strategies as generative AI (gen AI), as demonstrated by technologies such ChatGPT, is evolving rapidly. In 2024 the challenge will be to effectively leverage these new technology to improve customer satisfaction, drive positive business results and increase revenue.
Since its debut, a major revelation has been the unique roles that this new generation AI can perform, shifting from the traditional focus of analysis and classifying to the creation of creative content. Generative AI mimics human creativity by using neural networks and complex algorithms. It produces diverse outputs like text, images and music.
Generative AI, unlike artificial general intelligence (AGI), is task-specific. It offers practical solutions for its trained areas. It can handle various tasks with ease and adapt to new situations using incoming data.
What are the practical uses and limitations of Generative AI technology?
In reality, generative AI can be a powerful productivity tool. It allows rapid content creation in a variety of media, including images, sound, animations, 3D models, and text. It does not only remember and learn patterns and nuances of language, but also past interactions. This allows for more relevant and coherent exchanges between users and the AI.
Gen AI is currently not able to make decisions that involve many complex factors. This includes those that require a deep understanding of context or emotion. Although it excels at providing data-driven recommendations, integrating and managing human factors is still beyond its reach.
Will Devlin is the vice president of marketing for Customer Engagement Platform firm MessageGearsAI is a powerful tool that can help businesses and industries adopt it without worrying about failure.
Any marketer who’s ever done a standard A/B testing can tell you failure isn’t something that should be avoided. We learn new techniques, technologies and tools constantly in our careers. Fear of failure will always be part of the learning and growth process. “As with any new technology, AI has its own set of concerns that are real and relevant,” he told TechNewsWorld.
Understanding AI Path Forward
Michael Fisher is the chief product officer of digital compliance and data management company Complykey Waterfield Technologies (formerly Waterfield Technologies) has made four predictions in relation to these areas.
In the last year, contact centres, which were the primary users of this technology have quickly integrated generative AI. Fisher predicts 2024 will see a shift in focus towards a greater understanding of the ROI generated by generative AI.
He believes that contact center leaders, as well as other AI adopters, will increasingly focus on calculating AI’s cost in a more meaningful way. This effort also includes a greater understanding of how deployment costs can be optimized based on the scale and cost-per-transaction.
Manage Risks of AI Adoption at a Rapid Pace
Fisher’s second prediction is that Gen AI will be the most widely adopted in this year for marketing and prospecting customers, across industries. You must weigh the costs, benefits, and risks of lead generation.
In industries with high regulatory standards, such as health care, finance, and government, the inherent risks slow down adoption. In these industries, the back end of contact centers will aggressively use generative AI in summarizing and reporting data.
“On the front end of the customer, all verticals are going to move more slowly and deliberately.” He noted that the further away you are from industries like retail which are highly regulated we will see a faster adoption of generative AI.
Cloud and Video AI Solutions: Advancements
Many companies continue to offer both on-premises contact center solutions and cloud-based solutions, catering to the preferences of customers. Vendors incur a significant cost by maintaining both solutions. Do not choose one solution over another.
Fisher’s third prediction was that “in 2024, more companies will sunset their on-premises solutions or raise the price significantly to make an on-premises solution commercially unviable for customers — essentially forcing cloud adoption and innovation on customers.”
Insurance companies are the only ones who use video communications. AI tools for video conferencing can help automate note-taking and scheduling, enhancing productivity during virtual meetings. For example, they can show accident damage on a car or sign documents together. Video as a channel for customer service has been slow to catch on in most industries.
This will change by 2024. Fisher said that he expects video to become more widespread as a means of customer service in all industries, particularly for those who sell physical goods that can benefit from a demonstration, such as fitness clothing. Video demonstrations can show the flexibility, breathability, and overall performance of fitness apparel, helping customers make more informed purchasing decisions.
Specific use cases can help to drive demand for the feature. He said that Gen Z’s comfort with and familiarity of video-based content may help to change consumer preferences.
Precision in handling massive AI data sets
MessageGear’s Devlin thinks it is vital that as brands start to harness AI — particularly generative AI — they put guardrails in place and develop standard operating procedures and guidelines for their teams to follow.
It will be a process of learning. Gen AI cannot be a single-size-fits all solution.
He said, “I expect AI technology to only improve as we become more familiar with it.” “Because AI technology is so new, brands are still learning how to manage it, and make sure they use it responsibly, and to its maximum potential.”
A survey of enterprise brand marketers conducted by MessageGears recently revealed that the greatest challenges brands face in implementing AI solutions include limited expertise, staffing, and integration difficulty.
“AI modeling can only be as good as your data. Devlin said, “AI can also be a very powerful tool that helps brands improve conversions, ROI, save money, reduce time to value, improve testing, and learn.”
Human Insight and AI Technology: Integrating Human Insight
Shahid Ahmed is the group EVP of new ventures and innovations at digital consulting firm NTT Data‘s Global Customer Experience Report 2023 revealed that most CX interactions require some form of human interaction.
Executives agree that this will be an important part of the journeys for customers, according to this report. Even though 80% of companies plan to integrate AI into CX within the next year, the human factor will remain central to its success.
Ahmed told TechNewsWorld that “as enterprises begin to focus their attention on the ways automation can complement and improve human capabilities, more emphasis will be placed on resolving the growing skills shortages. This will pose a challenge to AI aspirations.”
He warned that new hires would not be the only way to acquire the basic skills of AI and Big Data Analytics.
NTT Data found that businesses who invested in reskilling or upskilling initiatives saw profits of 25 percent more over the past three-year period. He predicted that this trend would continue into 2024 with more curated learning experiences designed to close skills gaps and meet organizational needs.
Risks of DIY AI implementation
AI could be best leveraged in a combination of managed cloud. AI is everywhere. Adopters need to consider what numbers are used to chart this explosive growth.
Report by Cloud Security Provider Wiz The key link between AI services and a managed cloud platform is shown. The analysis of aggregated data from a large number of organizations gives a comprehensive view of the use of generative AI in the cloud, and how it impacts organizations.
AI has been gaining rapid ground in cloud environments, according to this research. Over 70% of companies now use managed AI. Wiz estimates that over 80% use managed Kubernetes.
Many organizations are still experimenting with AI, but they don’t go any further.
Only 10% of users are power users, who have deployed 50 or greater instances. The adoption of AI is increasing in the cloud, but many organizations still seem to be in an experimentation phase, with fewer than 10 AI services deployed in their cloud environments.
Predictive analytics: A powerful tool for Gen AI
Devlin of MessageGear observed that for most people, 2023 will be the year AI becomes a focus. People are now asking questions about how to best utilize AI. If they haven’t already begun using AI regularly, brands are now at the very minimum, AI-curious.
“They are eager to learn and explore. He noted that as brands get more comfortable with AI, he believes certain roles will become more complex while others will be made more efficient by AI tools.
When combined with insights from predictive artificial intelligence, generative AI is especially powerful. You know not only when and where your customers want to hear from, but also the likelihood of them making a purchase.
“It has almost unlimited potential, but brands have only just begun to use it,” he said.
