With a war raging in Europe and the world economy that is already reeling from the effects of the global pandemic, the debate whether a true recession is on its way is still ongoing. But apart from these troubles, one thing is certain: the economy is shrinking while borrowing has become more expensive than it has been in over a decade. Inflation remains at an all-time high, and businesses are preparing for a challenging time ahead. However, despite the economic slowdown, businesses are increasing their investments in the technology sector, and Artificial Intelligence (AI), has been one domain that is being seen as a dominant business driver.
Technology Investments on the Rise Despite Recession Fears
From big tech companies like Meta and Microsoft to giant corporations, businesses are becoming more cash-conservative and even scaling back their growth plans in order to ready themselves for the looming recession. However, businesses still need to consider investment areas that can improve operations and weigh where their investment dollars will give them the best and quickest ROI.
For this, technology executives claim that if they’ve learned anything from previous downturns, it’s that technology shouldn’t be viewed as a cost center but rather as a business engine, and in this sector, the primary areas being focused for investment include cloud computing, machine learning and artificial intelligence, and automation.
According to Nicola Morini Bianzino, the Chief Technology Officer at EY, “In other cycles we’ve seen in the past, tech investment was one of the first casualties, but after the pandemic, people realized that in a down, or even potentially, recessionary environment, we still need to keep our technology investments.”
Meanwhile, Danny Allan, Chief Technology Officer at data protection firm Veeam, said that “If you look at what occurred over the past two years, it’s clear that technology is the sustainable differentiator that sets companies apart.”
A recent report by CNBC cites J.P. Morgan’s annual chief information officer survey. According to the survey, the spending plans of 142 CIOs responsible for over $100 billion in annual enterprise budgets were compiled. The results found that IT budgets are growing, even if they’re not keeping up with inflation. For this year, the surveyed CIOs see IT budget growth of 5.3% and 5.7% in 2023. This is a major shift from when the survey was conducted during the global pandemic and IT budgets contracted by nearly 5%.
According to Guido Sacchi, the Chief Information Officer for Global Payments, the business and technology agendas have increasingly become one and the same. He claims that in his discussions with Global Payments business unit leaders, not a single executive has advocated that reducing tech spending is the best course of action in the event of a possibly severe economic downturn.
On the other hand, LinkedIn co-founder and Greylock partner Reid Hoffman, who was a guest speaker at a recent CNBC Technology Executive Council Town Hall, while speaking about AI, advised companies to stay invested but to do their homework. “Not everything is AI. Take the time to know where to apply it, how to make it work for you, and why it’s being used”, he said. He also stated that “You are sacrificing the future if you opt out of AI completely.”
AI Investments in Focus
According to technology research firm Forrester Research, which put out its budgeting and planning advice for corporate technology budgets for 2023, “global unrest, supply chain instability, soaring inflation, and the long shadow of the pandemic, all point to an economic slowdown.” It cautioned that “slower overall spending mixed with turbulent and lumpy employment trends will make it difficult to navigate 2023 planning and budgeting.” It has also advised that businesses search for methods to reduce spending, including doing so by getting rid of outdated technology. However, when it comes to investing in AI, the firm has suggested that companies should increase their spending.
Business leaders have been focusing majorly on investing in automation. In a survey by Bain & Company of 180 IT decision makers across North America and Europe, 41% of these respondents cited “building automation capabilities within business lines” as one of their most critical IT priorities. However, automation has its own set of problems, which is why business executives are now taking a major step beyond automation and into the world of autonomous artificial intelligence (AI) as they want to fully leverage their investments and see faster returns. True AI solutions that continuously learn from a company’s data and become more accurate over time are the holy grail of ROI.
AI Adoption and Impact
According to a report from the McKinsey Technology Council, investments in applied AI, which includes machine learning, computer vision, and natural-language processing, grew 150% between 2018 and 2021. The report also highlights that businesses spent $66 billion on applied AI technologies in 2018, as compared to $165 billion in 2021. In the compilation of the report, McKinsey collected data based on search engine queries, news publications, patents, research publications, and investments. The report also found that the business functions with the highest rates of AI adoption were product development, service development, service operations, and marketing and sales.
The report from McKinsey has also highlighted the fact that businesses saw cost reduction and revenue growth due to the adoption of AI. However, companies are still rattled by concerns pertaining to high up-front investments in talent and resources, cybersecurity and privacy concerns, increasingly stringent regulations, and compliance and ethical implications.
Another survey conducted in 2020 by McKinsey, titled “The State of AI in 2020”, highlights how AI adoption has impacted organizations. The results of McKinsey Global Survey on artificial intelligence (AI) suggest that organizations are utilizing AI as a tool for generating value. That value is increasingly coming in the form of revenues. A small group of respondents who are part of a variety of industries attribute 20 percent or more of their organizations’ earnings before interest and taxes (EBIT) to AI. These companies plan to invest further in AI, in response to the COVID-19 pandemic and its acceleration of all things digital. This could create a wider divide between AI leaders and the majority of companies still trying to capitalize on the technology. The survey also found that while companies overall are making some progress in mitigating the risks of AI, most of them still have a long way to go.
In the survey, the largest shares of respondents report increases in revenue for inventory and parts optimization, pricing and promotion, customer-service analytics, and sales and demand forecasting. More than two-thirds of respondents who reported adopting each of those use cases say its adoption improved revenue. The use cases that normally led to cost decreases were the optimization of talent management, contact-center automation, and warehouse automation. Over half of respondents who reported adopting each of those say the use of AI in those areas reduced costs.
Focusing on the Best – Maximizing Utilization of AI
According to the McKinsey global survey, the companies that saw the most value from their use of AI, that is, respondents who say 20 percent or more of enterprise-wide EBIT in 2019 was attributable to their AI use, reported several strengths that differentiate them from other respondents:
Better Overall Performance: The findings of the survey suggested that companies seeing more EBIT contribution from AI experience better year-over-year growth overall than do other companies. Respondents at high-performing companies are nearly twice as likely as others to report EBIT growth in 2019 of 10 percent or more.
Better Overall Leadership: Respondents at AI high performers rated their C-suite as very effective, more so than other respondents. They were also much more likely than others to say that their AI initiatives have an engaged and knowledgeable champion in the C-suite.
Resource Commitment to AI: Responses show that AI high performers invested more of their digital budgets in AI as compared to their counterparts and were more likely to increase their AI investments in the next three years. High performers also tend to have the ability to develop AI solutions in-house—as opposed to purchasing solutions—and they typically employed more AI-related talent, such as data engineers, data architects, and translators, than do their counterparts. They were also much more likely than others to say their companies have built a standardized end-to-end platform for AI-related data science, data engineering, and application development.
Benefits of AI
AI is more important and more transformative than any other type of technology and investing in AI has had significantly positive outcomes for businesses, including reducing costs, optimizing financial functions, and finding new revenue streams:
Reducing Costs
Business executives may drill down into their spending with the use of AI, which gives them visibility into their data across all business units. Instead of spending several weeks of time across multiple employees, AI reveals these insights automatically and thus enables business leaders to make strategic savings more swiftly than ever.
The cost reductions could also be significant if AI takes the role of some employees, such as those in customer service. An AI chatbot may work around the clock, is less expensive than hiring staff, and can increase customer satisfaction. Examples include Ibenta, Liveperson, and Ada.
AI can also lower costs by concentrating on predictive maintenance. Without AI, a mean-time-to-failure study is frequently used in machine maintenance to determine when to replace particular components. AI enables machines to report on their current state, helping to identify parts that are likely to fail soon and only repairing the parts in the devices that actually need to be replaced. Companies like H20, Dataiku, and Industlabs offer predictive maintenance capabilities.
Some healthcare providers are using AI for registration-related tasks, like ensuring the availability of a patient’s medical history. When this responsibility is removed from the staff members, employee efficiency is increased, and errors are significantly decreased. Error minimization is quite an expensive process as it may necessitate having employees redo tasks. Oliveai is one company providing solutions in this area.
In addition to saving companies money in terms of labor costs, AI also has benefits in terms of data and analytics. This is crucial in light of the fact that “leveraging enterprise-wide data and analytics to support strategic decision-making” was named a top IT priority by 50% of the surveyed IT decision-makers.
Optimizing Financial Functions
By deploying AI solutions in the accounting sector, finance professionals can lead the way in implementing digital solutions within their own organizations. Across industries, these teams are struggling with unending, tedious accounting tasks, employing obsolete, inefficient technology, and squandering a lot of time correcting mistakes made by individuals. Finance leaders can increase production and accuracy while freeing up their team members for more strategic work by implementing AI solutions.
In addition to this, there are huge benefits in doing real-time demand forecasting, inventory management, and accounts receivables using AI. Finance professionals can react extremely quickly to the changing environment and are able to predict where to allocate their funds as opposed to only responding to historical data.
AI also creates better predictive models, which enables a higher level of confidence in the store-closing decision process. With AI, you can layer in much more intelligence in your store-closing decisions.
AI can also assist in managing bad debt decisions. For example, in 2018, bad debt decreased profit margins by as much as 5% in many companies. Bad debt naturally increases during times of recession as customers delay payments or companies go out of business. With AI solutions, businesses can evaluate relevant customer data, such as credit rating, type of industry, payment history, debt burden, hiring and firing practices, geography, as well as many other data points to estimate the possibility of a company not paying their bills. Utilizing this information, an AI-based system can make real-time recommendations for the payment terms of such customers. Solutions include CognitiveScale, HighRadius, and YayPay.
Finding New Revenue Streams
AI has the capability to model expected consumer behavior which can help in enabling real-time promotions. Utilizing the historical results from promotions, AI can simulate buyer behavior by factoring in new variables, including governmental regulations regarding shelter-in-place, the opening, and closing of retail locations and schools, political affiliations, the possibility of a COVID-19 outbreak, and more.
AI also has the ability to collect data from the success of one promotion in one region and conduct similar modeling to suggest similar promotions based on real-time results in another location. Solutions include Revtrax, Antuit, and Vertica.
In addition to promotions, AI can help increase market share as well. AI can evaluate vast warehouses of data and identify patterns that humans can’t see. It can look at demographics, local consumer preferences, age, ethnicity, gender, income profiles, and many other things to find patterns.
Looking Ahead – The Future of AI
According to McKinsey, AI, and machine learning technology have promised US$600 billion annually for China’s economy as it pervades industries. The consulting firm is expecting AI to create an annual economic value equivalent to 3.7% of China’s current GDP as it finds its way into more applications. The report by McKinsey suggests that to unlock that value, further investments are required in data ecosystems, technology, talent, and business models, alongside standards and regulations.
On the other hand, two of the 14 most important technology developments taking place today are industrializing machine learning and applying AI, according to McKinsey’s recently published “Technology Trends Outlook 2022.” According to McKinsey, applied AI is based on tested and mature technologies, and it received the highest scores among the 14 trends on quantitative measures of innovation, interest, and investment due to its potential applications across a wider range of industries and its proximity to widespread adoption.
The percentage of respondents who indicated their firms have implemented AI increased from 50% in the 2020 survey to 56% in the 2021 McKinsey Global Survey on the state of AI. Product development and service operations are the corporate functions that have adopted AI most quickly, according to the 2022 research, while tech industries are leading in AI adoption.
According to Roger Roberts, partner at McKinsey and one of the report’s co-authors, economic issues won’t change AI’s strong, impactful momentum.
“There’s never been a better time to be leading the application of AI to exciting business problems,” he said. “I think there’s enough momentum and capability flowing along the path of science to engineering to scale.” He, however, also noted that within industries there may be some growing separation of leaders and laggards.
“Leaders will continue to make the right investments in talent tooling and capabilities to help deliver scale,” he said. “Laggards may let the opportunity slip away if they’re not careful.”
Roberts also added that he sees big tech companies such as Google, Meta, and Microsoft as in the lead on industrialized ML “by a longshot.” But he has predicted the trend would soon make its way well beyond those companies: “We’ll start to see more and more venture activity and corporate investment as we build that toolchain for this new class of software and this new class of product as productized services,” he explained.
In conclusion, the future years look set to be dominated by AI solutions being deployed across a wide range of industries in order to maximize efficiency and ensure continuous growth.
