Several challenges face businesses in 2024, including the labor market, climate change, geopolitics, and artificial intelligence (AI).
On the economic front, the International Monetary Fund (IMF) predicts that the likelihood of an economic soft landing has increased. Yet, the growth forecast remains the lowest for decades. Despite inflation trending lower, interest rates remain historically high, and it’s anticipated that the fallout from the Fed’s monetary policy will intensify in 2024.
Geopolitical uncertainties
Geopolitical uncertainties remain an unpredictable factor for the economy, particularly during a U.S. presidential election year such as 2024. According to a KPMG survey, CEOs now rank geopolitics and political uncertainty as the top risk to economic growth over the next three years, a significant shift from their seventh-place ranking in 2022, surpassing concerns related to supply chain issues and disruptive technologies:
“Every CEO, all the banks I am talking to, are factoring in geopolitics in their thinking in a way they didn’t five years ago,” said Frederick Kempe, CEO of foreign policy think tank Atlantic Council, at the CNBC Global Evolve virtual summit. “No one is saying it won’t affect business. ... Geopolitics is coming into the boardroom in a way it hasn’t in my lifetime.”
Amid turbulent geopolitical and economic conditions, corporate efforts will be made in 2024 to build resilient supply chains and data infrastructure to mitigate risks.
Against this backdrop, here is a look at some of the challenges and opportunities to watch in the coming year.
ESG oversight and accountability
It is becoming increasingly common for extreme weather events to disrupt manufacturing and supply chains and cause billions of dollars in economic harm.
As such, shareholders and stakeholders are demanding greater accountability from companies for the environmental, social, and governance (ESG) impacts of their operations. Doing business in an ethical and sustainable way also extends to a company’s global supply chain.
Value-driving ESG policies and practices are also gaining traction in M&A. A growing number of companies are leveraging ESG initiatives to boost profitability, revenues, and balance sheets for the combined business, enticing investors and boosting shareholder returns.
Companies are also working to reduce their carbon emissions. However, these endeavors risk a higher likelihood of regulatory fines for their sustainability claims. U.S. and European regulators are expected to aggressively scrutinize company’s ESG assertions with new disclosure and labeling rules and increased enforcement.
In 2022, the SEC issued a proposed rule to enhance and standardize the climate-related disclosures of public companies. Companies will be required to report global warming threats, their impact on business strategies, and how executives and corporate board members will manage those risks. Crucially, companies must also account for their greenhouse gas emissions.
Regardless of whether the rule will be adopted as drafted or modified, publicly traded companies must determine how they will satisfy disclosure requirements. Even non-publicly traded companies should be aware that investors and lenders will view these rules as a guiding principle when making investment decisions.
Generative AI and LLMs: Developing use cases and a governance framework
Generative AI, such as ChatGPT, and large language models (LLMs), will be transformative in 2024. LLM is a form of AI that uses deep learning and big data sets to understand, summarize, generate, and predict new content.
Generative AI will continue to surge in popularity as barriers to entry lower and vendors embed it in their products and services. LLM will play a pivotal role in promoting adoption, enabling employees to access information in a conversational manner.
A recent survey of chief data officers by Amazon Web Services, found that 80% of respondents agree that generative AI will transform their business.
The use of generative AI capabilities will further elevate the importance and utility of an organization's unstructured data, encompassing documents, videos, and content housed within learning management systems. This innovative technology has a broad range of use cases, spanning software code generation, risk assessment, marketing, and customer support.
But companies must also consider the risks that AI models and applications introduce, such as algorithmic bias due to imperfect training data or decisions made by developers. And, as companies incorporate AI models and tools from external providers, they inherently acquire the extensive datasets employed in training those AI models. This may lead users to inadvertently accessing sensitive information contained within the vendor’s AI models, which could result in regulatory, commercial, and reputational repercussions.
Furthermore, security issues can occur. Personal data may be leaked, cyber criminals can use LLM for phishing and spamming, and hackers may change original programming.
A strong governance framework is needed to mitigate these risks, minimize regulatory scrutiny, protect the business, and earn customer trust. To limit liability, CEOs must also stay current with generative AI regulations, including consumer protection laws and intellectual property rights.
Importantly, companies can mitigate bias and reduce risks by keeping humans at the center and ensuring quality data within these models.
Closing the talent gap
The workplace will continue to transform rapidly in the coming years and businesses that have reduced headcount or frozen hiring may find themselves facing a talent shortage. Another alarming emerging trend is boardroom succession planning. As directors and C-suite members near retirement, replacing them with younger talent will become imperative.
To close the talent gap, many organizations are increasing salaries and improving benefits, including bonus programs, medical plans, and well-being options. While compensation is key, career development opportunities, workplace flexibility, and inspired leadership are key to employee hiring and retention.
In addition, AI will help businesses in certain industries realize opportunities for cost savings and automate workflows – both of which can help manage the talent gap.
Even as the emphasis on technology skills intensifies, it's important to remember that leaders are still responsible for guiding and managing people. Consequently, the need to inspire, motivate, and foster a stronger sense of belonging will remain a priority in the upcoming year. Employees who are treated as part of the team report greater levels of job satisfaction and are more likely to perform well over the long term.
Outsourcing and managed services can also solve talent gaps and other business pain points in the interim.
