2023 will be the Year of AI. Publications often mark a year with a name most closely associated with the biggest events of that year. Although AI has been with us for decades, generative AI has made AI into a productivity tool for everyday users.
Special Feature
Generative AI is changing everything: saving time, empowering people to produce work they otherwise don’t have the skills for, opening new doors for opportunities, and more. But there’s a dark side. Workers are worried employers might replace them with lower quality yet more inexpensive, AI-generated output.
There’s also an accuracy problem. Generative AI systems are often wrong, and the more people rely on them, the less folks will double-check the results.
Also: We’re not ready for the impact of generative AI on elections
Generative AI is just one aspect of AI currently being employed. We spoke via email to an army of executives and selected six stories that showcase a variety of AI applications and benefits already in play. These six spotlighted companies are leveraging AI to fundamentally transform traditional practices and norms in their respective industries. Their adoption of AI is leading to enhanced efficiencies, safety, customer experiences, and overall innovations.
The executives from these six companies told ZDNET how they were currently using AI, how AI has transformed their processes, and what benefits they were seeing. Special thanks to the executives for their time and in-depth answers.
Ericsson: AI in the telecommunications sector
- Problem: Workplace injuries
- AI technology: Computer vision
- Benefit: Enhanced worker safety
Ericsson Safe Work is part of telecommunications giant Ericsson. Vivek Gnanavelu, founder and CEO of Ericsson Safe Work, tells us, “In telecommunications, where tower-related deaths outnumber those from general construction, Safe Work shields crews.” He says this helps to eliminate workplace injuries and fatalities.
Despite safety protocols, many accidents occur when installing or maintaining cell towers, antennas, or radios. Since its inception, Gnanavelu reports, “We’ve seen remarkable AI-driven efficiencies with internal customers. Across key metrics, such as crew time saved, AI-detected non-compliances, and AI-assisted approval percentage for safety forms, significant efficiencies have emerged.”
The company uses computer vision and AI models to validate worker compliance with Personal Protective Equipment (PPE) standards, such as helmets, gloves, vests, and work boots. It also provides live weather alerts and risk assessments. AI systems then provide continuous monitoring and live vital tracking, ensuring workers’ readiness for tasks.
On a larger scale, the company’s AI pattern recognition powers automated reporting and large-scale data analysis to learn and prevent future repeat incidents.
SoFi: AI in banking
- Problem: Slow customer service
- AI technology: Conversational AI
- Benefit: Instant accurate, and empathetic responses
SoFi delivers member-centric digital financial services to help more than six million members “achieve financial independence.”
We spoke to Aaron Webster, chief risk officer and global head of operations in Latin America, who tells ZDNET, “SoFi’s AI solution is not a chatbot. It adopts an intelligent digital assistant model that comprehends customer emotions, enhancing experiences. Unlike basic chatbots, the assistant employs advanced natural language processing, providing a human-like interaction with real-time adaptation, seamless handoffs to agents when needed, and personalized responses.”
SoFi integrated Cyberbank Konecta, a conversational AI engine offered by Galileo Financial Technologies affiliates, into their existing tech stack with the goal of enhancing their member experience with automated agents. SoFi is using this conversational AI engine to handle customer inquiries outside the hours their customer support team could offer alone.
Webster tells ZDNET, “We are leveraging conversational AI with empathy to tailor each member interaction in real time, infusing a human touch when needed, to enhance our member experience while reducing operational service costs by effortlessly managing common inquiries with AI.”
He says that since deploying this solution, response time increased by more than 65%, and half as many customers dropped out from their chat interactions. He said that thousands of conversations are now resolved without the need for transfer to a human agent.
Hexagon: AI in the public safety sector
- Problem: Vast public data
- AI technology: Assistive AI
- Benefit: Crime prevention and data analysis in real-time
Hexagon AB, headquartered in Stockholm, is a €5.2 billion multinational company that services municipalities. Kalyn Sims, chief technology officer for Hexagon’s Safety, Infrastructure & Geospatial division tells ZDNET, “Data intelligence is valuable, but being able to share and act on that information in real-time is vital. Assistive AI is a key technology to help organizations manage the explosion of data we’re facing today.”
In this context, assistive AI helps human operators process vast amounts of data by sifting through it and identifying important patterns, correlations, or anomalies that might be missed or would take a long time for a person to identify.
Hexagon’s Safety, Infrastructure & Geospatial division improves the resilience and sustainability of critical services and infrastructure. Their technologies transform complex data about people, places, and assets into meaningful information and capabilities for better, faster decision-making in public safety, utilities, defense, transportation, and government.
Hexagon uses assistive AI to help agencies fully realize real-time data, according to Sims, “Before the information becomes irrelevant.” Assistive AI uses advanced statistics and machine learning to mine an organization’s operational data to detect anomalies that require immediate action.
For example, assistive AI helps police, fire, and EMS to detect and respond to complex emergencies sooner. It works in the background and aids 911 dispatchers by seeing patterns and determining if public safety events are linked. Because it is assistive, it only alerts dispatchers of the anomalies, leaving the decision-making about resource deployment up to humans.
The public safety sector is a high-stress environment, and the industry is currently suffering from staffing challenges. With more calls for service from the public and more data coming in from surveillance cameras, traffic sensors, IoT devices, and more, users can become overwhelmed.
New collaborative AI capabilities, according to Sims, can solve that problem. By using smart technologies to update legacy systems, it takes the pressure off overworked crime analysts and dispatchers by sifting through incoming real-time data, looking for trends and anomalies, and providing users with alerts in the moment.
The net result, says Sims, is that “This autonomous initial assessment resulting from assistive AI technology is much more efficient, effective and scalable than the manual monitoring and analysis of information from multiple calls from the public, sensors, and alarms.”
Revolear: AI in B2B sales
- Problem: Complex B2B sales
- AI technology: AI optimization
- Benefit: Transformed sales process
Revolear provides tools for very complex B2B sales. Founder and CEO Raja Singh says, “Is a cutting-edge digital deal platform infused with AI that transforms the way companies structure, propose, negotiate, and approve complex business solutions.”
Revolear uses AI in its product as well as in its development process.
The business-to-business selling process can often take months for complex deals, and involve many twists and turns. Not surprisingly, there are ample opportunities to apply AI in many of its forms. Revolear uses generative AI to distill customer requirements and generate tailored, role-specific sales proposal text. They use machine learning to predict optimal discount levels and other deal terms, and create weighted metrics around deal momentum and approval probabilities.
Revolear’s development team uses the Copilot tools in GitHub to help with coding. Singh says it doesn’t replace the engineer, but can complete a line or contribute a code snippet. He says, “we also use generative AI to refine our marketing copy. We don’t use it to build the storyline, but it can proofread and improve sections. One really useful application is generating fictitious demo data. Our products look better with realistic data, and ChatGPT can produce it at high volumes.”
Singh reports that AI has reduced the friction on one of the hardest parts of the sales process. “One of the most nerve-racking decisions a sales team has to make is setting their initial asking price. Historically, the sales team relies on their experience. Now, we’ve built machine learning models with as few as 50 rows of data to predict final prices.”
Abpro: AI in biopharmaceuticals
- Problem: COVID-19 treatment
- AI technology: AI-driven discovery
- Benefit: Speeds drug experimentation process
Abpro is a biotechnology firm developing monoclonal antibody therapies in the cancer, eye care, and infectious disease spaces. They have developed one of the key treatments for COVID-19.
Abpro CEO and co-founder Ian Chan explains that AI is helping in the fight against COVID. “A continuous challenge with COVID-19 is the inability of treatments to keep up with changing variants. Abpro is deploying AI to do just that.”
With AI, he says, the company is able to predict the evolution of the spike protein, as well as other regions of the virus, making for a more future-proofed treatment. Abpro is able to develop monoclonal antibodies without solely relying on in vitro experiments by combining tested biochemical measurements and antibody generation from real experiments, then utilizing that data to train the antibody’s predictive capabilities and enable it to keep up with evolving variants.
He tells ZDNET that AI can assist in the identification of new drug targets, designing new drugs, and accelerating the overall drug discovery process. AI is streamlining complex tasks such as expediting the design and optimization of antibodies.
Using machine learning models, companies can now enhance specific antibody properties including how an antibody binds to a target, as well as its solubility, immunogenicity, and yield. AI is also being used to predict pathways for producing theoretical drug compounds, with the ability to suggest modifications to those molecules, which would make them easier to manufacture.
The time savings using AI are considerable. Traditionally, monoclonal antibodies were discovered through experimental techniques, such as the hybridoma technique, or by using a phage display. According to Chan, “By harnessing the power of AI, biopharma companies, like Abpro, can cut an approximate eight-week experimental process into a single afternoon.”
The Digital Panda: AI in a creative agency
- Problem: Manual design mockups
- AI technology: Midjourney and ChatGPT
- Benefit: Rapid design mockups
The Digital Panda is a small creative agency developing branding, web, mobile, and motion design. The company uses off-the-shelf cloud AI tools like Midjourney and ChatGPT to help with their creative process. They use Midjourney to create rapid high-fidelity storyboards for motion. They also use ChatGPT on their development team to support coding and bug fixing.
Ilya Kroogman, The Digital Panda founder, tells ZDNET, “We utilize LLMs to improve our copywriting output and automate the way we post our own work on various social platforms.”
Kroogman adds, “Using Midjourney has also allowed our creative team to rapidly streamline our ideation phase for mood board and storyboard development. Previously, we would need to spend hours on ideation, sketching, and conceptualization, where now we can simply tell the model our ideas, then iterate almost instantly.”
Fundamentally, Kroogman credits generative AI with helping, “Make our organization feel and operate as a much larger one.”
Organizational transformation through AI
Executives are also weighing in on the sudden adoption of generative AI among organizations. “Generative AI is a fascinating technology but still very new,” says Jiani Zhang, executive vice president and chief software officer of Capgemini Engineering — its parent company Capgemini is a multinational IT services and consulting firm with offices in at least 50 countries.
“Many companies are experimenting with GenAI for its potential to accelerate the development of use cases across knowledge management, support, and even code generation,” she tells ZDNET. “Despite the growing prominence of GenAI, degrees of adoption vary — primarily because of reservations trusting the integrity of the generated content.”
Zhang provided three recommendations for adopting AI into organizations:
- New processes must be put into place to navigate the regulatory and ethical aspects of AI development with code generation.
- Organizations and users alike must be able to trust the generated content, and therefore experts must ensure the validity of the large language models (LLMs) being rolled out.
- This will require implementing new processes during the development lifecycle with methods for validation of the generated content.
Meanwhile, Slalom, a business and technology consulting company with offices on four continents surveyed two hundred C-suite executives from across the US on their 2023 AI investments and 2024 sentiments. The comprehensive survey of business adoption shows how organizations are using AI now and where they may go in the future. The results also showed two conflicting statistics.
First, the survey found 71% of executives don’t fully comprehend the scope of tasks Al can effectively augment or automate in their organizations. Those tasks include work in the following sectors:
- Organization and Workforce: Adapting workforce and culture for AI collaboration.
- Technology and Data: Essential tools, platforms, and datasets for AI.
- Business and Customer Value: Enhancing customer experience and market value with AI.
- Strategy Alignment and Orchestration: Integrating AI into business strategy and operations.
- Security, Ethics, and Governance: Ensuring ethical, secure, and governed AI practices.
Second, while executives don’t fully understand where this AI thing is going, 87% have begun AI adoption or transformation initiatives.
“Most companies we talk to have already made AI investments such as AI chatbots for customers or internal training to improve how employees work, says Tony Ko, managing director of business development and advanced analytics at Slalom Consulting. “These investments are table stakes for them to remain competitive.”
But Slalom’s survey also shows that 61% of executives say their companies are struggling with the pace of AI advancement.
“The biggest challenge is knowing where to go next. Leaders are asking for help to build their longer-term visions and determine the investments they need to make to stand out from their competitors,” Ko added.
Consequently, Slalom’s survey revealed a full 70% of executives plan to increase resource and budget allocation toward AI in 2024.
This encapsulates how AI is not just an add-on but a pivotal force driving change, revolutionizing sectors, and redefining what’s possible in both traditional and new-age industries.
What does it all mean?
If you think AI is big in 2023, it will be huge in 2024.
Ali Minnick, Slalom’s General Manager of Global Business Advisory Services, tells ZDNET, “Many companies didn’t budget for large-scale AI transformation efforts in 2023 given the concerns about the possible recession. Those concerns haven’t changed, but many are preparing to spend more on AI in 2024. Their fear of falling behind outweighs the economic uncertainty.”
That certainly holds true across the six companies we spotlighted. Across Ericsson, SoFi, Hexagon, Revolear, Abpro, and The Digital Panda, here are the common themes related to their AI use:
Enhanced efficiency: Both SoFi and Hexagon utilize AI to speed up traditionally manual processes. For SoFi, this means faster customer service, while for Hexagon, it translates to quicker data processing for public safety.
Improved decision-making: Hexagon’s assistive AI provides insights for public safety agencies, aiding in making informed decisions that can prevent potential risks or threats.
Customer-centric solutions: SoFi’s integration of a conversational AI platform to enhance customer service and Revolear’s optimization of the B2B sales process both demonstrate a commitment to improving customer or client experiences.
Safety and compliance: Two companies, Ericsson and Hexagon, stand out for their commitment to leveraging AI for safety. Ericsson focuses on workplace safety while Hexagon emphasizes public safety and crime prevention.
Innovation in traditional sectors: Abpro’s AI-driven approach to drug discovery in the biopharmaceutical industry and Ericsson’s application of AI in telecommunications highlight the transformative potential of AI in long-established sectors.
Adaptive learning and evolution: The Digital Panda’s use of AI for rapid design mockups exemplifies how AI-driven solutions can evolve and adapt to provide better results over time.
Challenging the status quo: Companies like Revolear and Abpro are using AI to redefine norms in their industries, from B2B sales to drug discovery.
Holistic solutions: Ericsson’s comprehensive approach to ensuring worker safety, by integrating AI, computer vision, and IoT, demonstrates a holistic use of technology to address complex issues.
In essence, these themes emphasize the transformative potential of AI in diverse sectors, from banking to biopharmaceuticals, and its role in driving efficiency, safety, and innovation.
Kevin McClelland, general manager of Slalom Build sums up the situation perfectly, saying, “Many organizations find adopting generative AI to be like trying to jump on a moving train while blindfolded. They feel the urgency to move but it’s hard to do, and they’re not sure if it will even take them in the right direction.”
It is clear that the moving train isn’t going to stop. We’ve reached a massive tipping point in what AI can do for individuals and businesses. Keep reading ZDNET and Special Features articles like this one, so we can help you take off the blindfolds and see clearly where this technology is heading, focus on making the right decisions, and give you a clear heads up for pitfalls ahead.
What do you think? How has your business adopted AI? Let us know in the comments below. And be sure to read other articles in this Special Feature. Each one tackles the issue from a different perspective and has powerful insights you can integrate into your strategy right now.
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