Engineering product firms were among the first to embrace AI and machine learning. And the early adopters are reaping gains, finds Sangeeta Tanwar.
As technologies such as artificial intelligence (AI) and machine learning (ML) mature, innovation is no longer the sole domain of consumer-facing businesses. With democratisation of technology, organisations in the business-to-business (B2B) space -- traditionally deemed as slow adopters -- are enthusiastically embracing AI technology.
The objective is to offer advanced and responsive products and services to clients.
For example, with the help of AI and ML, Otis is developing smart elevators capable of communicating with passengers, building managers, service staff and other building systems. The elevator manufacturer is transforming its service business to incorporate smart, connected technology that delivers proactive, quick and effective diagnostics and repair.
"The transformation is an investment in digital tools, mobility solutions, apps, IoT [Internet of Things] and operational excellence to enhance customer experience, accelerate business productivity and increase employee engagement. Future development in elevator technology will draw heavily on digitalisation," says Otis India president Sebi Joseph.
For instance, Otis's CompassPlus Destination Management System evaluates real-time passenger traffic to improve flow and travel time in busy mid- and high-rise buildings.
Construction and agriculture equipment manufacturer JCB India is another B2B player that has been quick to leverage AI and IoT for strengthening business processes.
As the pace of building infrastructure gains momentum, there are growing cases where each customer owns multiple JCB machines. These machines largely work in remote parts of the country. In such a scenario, managing a fleet of machines to get updates in terms of performance, usage, fuel consumed and maintenance of the machine through mobile phones turns out to be a complex task.
In order to simplify the process of tracking multiple JCB machines, the company has developed an AI and ML-led solution called Livelink. Each machine is fitted with hardware that relays information sensors in real time about the location and performance of the machine. Each machine uses mobile data for communication with a command centre based at the JCB factory.
The dealers also have access to this information through local command centres set up at JCB dealerships.
"Using the Livelink solution and an easy-to-use website, machine owners [contractors or hirers] can now 'see' their machines electronically on a map and have real-time information about their fleet. This helps them immensely in managing service schedules and also in optimising and managing fuel usage," explains Vipin Sondhi, managing director and CEO, JCB India Limited.
Even as B2B businesses invest in AI solutions, it takes time to realise returns. Hence, organisations must be willing to commit to the resources and time required for benefits.
According to Sudhir Jha, senior vice-president and global head of product management and strategy, Infosys, AI-powered predictions are based on a probability of likely outcomes and there is always a margin of error.
The acceptable margin of risk varies by use cases. For example, the margin of error for medical diagnosis needs to be extremely low because lives depend on it.
"These use cases will leverage AI technologies to help humans narrow down choices as opposed to full or partial automation. But a product recommendation or customer churn analysis can be less precise and still have large impact," says Jha.
Most of the AI use cases in the B2B space are in areas like sales, marketing and customer service departments.
For instance, at Xerox AI-led solutions are being deployed to better understand customer needs and enhance service delivery. Xerox WDS Virtual Agent taps into intelligence gleaned from terabytes of data the company keeps about customer interactions. Armed with the info, the virtual agent can more reliably solve problems, as it learns through experience.
Says Ritesh Gandotra, director, GDO sales, Xerox India, "AI can understand, diagnose and solve customer problems without being specifically programmed to give rote responses. It analyses and learns from human agents. Our technology helps overcome one of the key barriers brands face in trying to deliver a truly omni-channel care experience, the ability to be consistent."
Digital care tools often lag behind the intelligence in the contact centre, with outdated content or no awareness of new problems. However, AI and ML are changing this.
In the building and automation industry, for instance, analytics and IoT is not only making service delivery processes more efficient and customer-centric, but also reducing labour costs to a large extent.
Honeywell Building Solutions (HBS) has recently launched the Outcome Based Service (OBS), utilising analytics and IoT to predict failures that could hit a building's sub-systems. Using OBS, the system automatically detects possible future breakdown scenarios, raises an alarm, and notifies the respective service team on real-time basis so that the necessary action can be taken.
AI can help build a smart suite of services focused on maintenance activities for optimal facility performance. IoT can be used for enabling visibly better operational performance for bottom-line impact and generating year-over-year value from a building, says Aseem Joshi, regional general manager, HBS India.
Hewlett Packard Enterprise has taken to AI for delivering workload-optimised computing solutions for deep learning through its HPE Apollo portfolio that claims to maximise performance, scale and efficiency.
"The requirements of today's business go beyond superior performance and efficiency as they are increasingly considering security, agility and cost control," says Vikram K, senior director, data center and hybrid cloud, Hewlett Packard Enterprise India.
It has also launched a new generation of HPC and AI systems, software and services to deliver faster, more efficient insights while reducing vulnerability to cyberattacks and improving economic control.
According to a survey by Demandbase, only 10 per cent of the non-consumer facing companies are adopting AI. But 80 per cent feel AI will revolutionise business by 2020.
Nandavarapu Kiran, director, hi-tech practice, Blueocean Market Intelligence, is of the view that companies are slowly warming to the idea of exploring AI as they believe it will help them to target customers in real time, generate higher lead conversation, personalise marketing campaigns, offer insights using the customer resource management platform and automate routine tasks.