AI whiplash: navigating the surprising aftermath of the pandemic

As the pandemic began to upend the world last year, businesses reached for every tool at their disposal—including AI—to solve challenges and serve customers safely and effectively. While every organisation will need its own playbook to recover from the AI whiplash and optimise its investment in the technology, a comprehensive plan should include five components:

A strategic investment in data

In a digital organisation, data is the connective tissue and raw material of AI. For AI models to be trained, organisations need clean, machine-digestible data labelled by subject matter experts. They require a data storage infrastructure that transcends business silos and delivers data quickly and reliably. As soon as the models are deployed, a strategy and approach to collecting data are required to continually train and tune them.

The right talent

Scientists with expertise in artificial intelligence are in high demand and hard to come by -- but they are crucial to understanding the AI landscape and guiding strategy. Organisations without a full team of scientists will need external partners that can fill in the gaps and help them sort through the ever-expanding array of AI vendors and offerings.

A long-term AI strategy guided by the business

Rather than buying technology and trying to figure out how to use it, organisations get the most out of AI by finding solutions to problems instead of buying it. They let the business drive the agenda, not the IT department. The failures of AI investments linked to business strategies can lead to opportunities for learning rather than fast failures. However, companies must iterate quickly within a long-term AI strategy, because the biggest benefits are realised over time.

Culture and employee upskilling

Without buy-in from the workforce and a culture devoted to AI's success, AI agendas will fail to gain traction. To gain the commitment of your employees, you have to provide them with at least a rudimentary understanding of the technology and data, as well as the benefits it will provide them and the organisation. Additionally, upskilling the workforce is crucial, especially where AI will take over or supplement their current responsibilities. It will be easier for an organisation to scale and succeed if it focuses on data-driven culture and a deeper understanding of artificial intelligence.

A commitment to ethical and unbiased use of AI

AI holds great promise but also the potential for harm if organisations use it in ways customers don't like or that discriminate against some segments of the population. Every organisation should develop an AI ethics policy with clear guidelines on how the technology will be deployed. This policy should mandate measures and be part of the DevOps process to check for issues and imbalances in the data, measure and quantify unintended bias in machine learning algorithms, track the provenance of data, and identify those who train algorithms. Organisations should continuously monitor the models for bias and drift and ensure explainability of model decisions are in place.

How things will unfold

Different industries have different objectives for investing in AI in the next two years. In terms of robotic tasks, telemedicine, and patient care, healthcare executives plan to focus on these areas. AI will be used in life sciences to identify new revenue opportunities, cut administrative costs, and analyse patient data, according to the company. Government executives say they plan to improve process automation and analytics as well as manage contracts and other obligations.

Additionally, industry-specific expectations differ. Customer intelligence, inventory management, and customer service chatbots will have the most impact, according to retail executives. Product development, engineering, maintenance, and production are some examples of how industrial manufacturers understand it. Additionally, firms in the financial services industry anticipate getting better at fraud detection and prevention, risk management, and process automation.

Over the long run, AI will play a critical role in reducing fraud, waste, and abuse, as well as helping businesses optimise their sales, marketing, and customer service. At the end of the day, we believe that AI will help resolve fundamental human challenges in areas as diverse as disease identification and treatment, agriculture and global hunger, and climate change.

A future like that is worth working toward. Government and industry both have a role to play in facilitating this - by collaborating to develop rules that encourage the ethical evolution of AI without stifling the innovation and momentum already underway.