Recession and AI investments

It’s no secret that AI and machine learning have the potential to help businesses navigate economic downturns by reducing costs and boosting efficiency.

In a world where the economic landscape is often unstable, businesses find themselves under constant pressure to thrive and evolve. We understand that the thought of a recession is unsettling, and you may be questioning if now is the right time to invest in AI and machine learning. In these challenging times, it’s more critical than ever to stay ahead of the curve and use all tools at your disposal to ensure success.

If you’re currently reviewing your AI strategies, here are a few key things to keep in mind:

• Be practical about implementation timescales, as AI projects often take longer than expected to get into action.
• Clearly define business benefits, outcomes, and KPIs for each AI project. Scope your projects based on the level of understanding of business benefits, potential revenue increase, cost reduction and risk mitigation.
• Understand inherent expenses and challenges associated with AI projects. These include process preparation, data handling, staff upskilling and organizational readiness. A lack of established process flows and data readiness could result in unforeseen hurdles before seeing AI benefits. Organizational inertia towards change poses significant challenges when deploying an AI solution.

Many managers may lack the necessary leadership skills to handle AI in their organization (as described in “The Seven New Leadership Skills” blog post). Also, introducing AI could call for changes the company isn’t ready for. These issues could cause delays and affect the business benefits. Addressing these challenges is ever more crucial in tough economic times.

• Invest in your data science and AI/ML abilities: When the economy is going through a dip, skilled individuals may become available to hire due to redundancy from other organizations. At the same time, remember that in-demand talent might shift towards essential projects. Fully grasp the extent of your reliance on your data science and AI/ML expertise and the implications losing some could have on your project. Also, think about how you want to present your AI/ML and Data Science hub to make it appealing for people to come on board.
• Realistically assess “blue sky” projects: Some companies have numerous exploratory AI/ML projects for gaining experience and, in some cases, projects that are often overambitious. While preparing for a possible economic slump, companies should be practical about less defined or speculative projects and redirect resources to AI projects that ensure clear business advantages.
• Be explicit about integration: Every AI project needs to intermesh at one level or another with other aspects of the company’s technology framework beyond simple data integration. Carry out a risk evaluation focusing on cost optimization that covers all integration points between the AI project and the entire software structure. The Essential components the AI projects blend with might be postponed or canceled due to cost optimization – understanding these risks beforehand is crucial.
• Develop relationships with your third-party AI solution providers and software vendors: In recessionary times, partners such as integrators, consultancies, and software vendors also feel the strain. Assess their current status based on their economic situation and existing clientele. A robust customer base signals a provider’s ability to survive an economic downturn.

In the upcoming years, artificial intelligence will revolutionize various workplaces, from how we handle business processes, interact with customers, manage supply chains, and work within our ecosystem. However, staying prepared for any unforeseen economic setbacks within this time frame is crucial. To tackle such situations, organizations should prioritize safeguarding their key AI projects. As the digital shift continues to reshape organizations, it’s essential for them to reassess all project avenues consistently. Yet, considering AI’s potential future significance, CEOs should concentrate their attention specifically here for a smoother journey ahead.

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