Editor’s note: AI Impact is Newsweek’s weekly newsletter exploring how business leaders are extracting value through artificial intelligence.

Core Intelligence: AI and Enterprise Budgets

AI is presenting a challenging question for enterprise technology budgets: what to cut to make room for new advancements? Many organizations are boosting technology spending, yet it’s often insufficient to cover all needs. AI, data modernization, older system upkeep, and digital work all vie for limited resources.

Noshir Kaka, senior partner at McKinsey & Company, noted the dilemma in a conversation with Newsweek before the upcoming “AI Impact Forum” webinar with Dr. Ranjit Tinaikar. He highlighted how traditional systems feel the most strain when funds shift towards AI innovations without a proportional increase in resources.

“If you’re increasing your budget by 6 or 7 percent, but you need 20 percent more capacity to meet demand, that gap has to come from somewhere,” Kaka said.

Companies want to develop AI capabilities but must also maintain existing systems. The reallocation of funds to AI, data, or modernization exerts pressure on older technologies, vendor contracts, and projects deemed less central.

Spending assessments change when leaders must deliver measurable results. This raises scrutiny on each section of the tech budget, including maintenance spending previously seen as indispensable. Older systems, while essential, are more vulnerable without protection.

The AI boom places incumbents in an uncomfortable position as customers seek more without unlimited new spending. Services firms, software providers, and platform companies anticipate a larger market but aren’t receiving additional funds upfront. Customers want providers who can optimize constrained resources and demonstrate the investment’s trajectory.

The Opportunity and Competition

The services economy grows more attractive yet more unforgiving. AI broadens the market for software and services, inviting more competitors into the same space. Services firms move towards software-like offerings, software companies incorporate service-like capabilities, and startups target niche workflows without legacy business models. Winning companies will not merely sell to AI demand; instead, they’ll guide clients on funding priorities and connect tech spending to outcomes.

AI propels companies to address issues beyond technology updates. It’s easier to upgrade systems and data than to redesign decision-making, operations, and workflows.

“Modernizing the tech and data stack is getting easier,” Kaka remarked. “Reimagining how work gets done—and how organizations operate—is not.”

Incremental productivity gains may not meet expectations tied to AI investment. Companies seeking substantial improvements must approach AI as more than another software layer. They must reassess processes, incentives, and investments to ensure technology delivers real value.

“Going from 5 or 7 percent productivity to 50 or 60 percent is not a small adjustment,” Kaka added. “It requires fundamentally rethinking how the organization works.”

Companies best positioned may not have the largest tech budgets but show willingness to make hard choices within them.

You can read the article and sign up for the upcoming webinar here: Who Wins in the AI Services Economy? Join Our Webinar Discussion.

Upcoming Webinars

The Trillion-Dollar Question: Who Wins and Who Loses in the AI Services Economy?
AI accelerates enterprise decisions, compelling leaders to rethink tech spending and productivity. In the AI Impact Forum session, Dr. Ranjit Tinaikar and Noshir Kaka discuss reshaping enterprise spending. Register for the discussion on Thursday, May 28, at 10 a.m. Eastern.

AI in Finance: From Individual Adoption to Enterprise Transformation
Financial services face challenging AI questions beyond productivity. Dr. Ranjit Tinaikar and Kevin Buehler examine agentic AI’s impact on finance during an AI Impact Forum session. Join live on Thursday, June 18, at 9:30 a.m. Eastern.

Prompt Injection

What’s one recent insight you’ve learned about AI?

AI’s memory about you matters more than model specifics, according to recent insights from Adam Mills. Individuals often focus on perfect prompts or selecting smarter models, forgetting AI assistants reset memory between conversations.

Mills developed AI workflows at Botify, utilizing four text files to drive improvements: memory, voice, insights, and company data. Capturing these helps AI start sessions oriented, lowering re-explaining and increasing productivity.

“The trick is instructing AI to update these files itself after each conversation, logging changes, decisions, and lessons. You don’t manage AI memory; AI manages itself,” Mills explained.

Understanding your preferences, history, and status means AI functions as a collaborator instead of merely a tool.

Run Log

AI use case of the week…
Cancer screenings face scale and comfort challenges. SpotitEarly addresses detection using dogs’ ability to smell disease. Their platform, LUCID, integrates AI with trained detection dogs. Patients provide breath samples, and dogs’ reactions are recorded for AI interpretation.

“AI is most useful when it does something biology cannot,” said Shlomi Madar, CEO of SpotitEarly.

While dogs provide the detection signal, AI standardizes it. The platform achieved 94 percent accuracy across several cancers in clinical trials, outperforming dogs alone.

Context Window

• Anthropic acquired Stainless to enhance Claude’s API connectivity.
• Google’s AI processes over 3.2 quadrillion tokens monthly.
• Verizon reports generative AI aids attackers in data breaches.
• AI competition has no clear finish line, per policy experts.
• Enterprises face strategic choices between renting AI and building systems.
• Meta restructuring includes AI focus and layoffs.

Transfer Protocol

• Albert Chan appointed president and chief AI officer at Rowland AI.
• Nicole Reineke becomes chief AI officer at N-able.
• Raviv Levi joins CData Software as chief product and technology officer.
• Matt Wood returns to AWS as chief AI and technology officer.
• Mary-Anne Williams appointed chief AI scientist at Commonwealth Bank of Australia.
• Doug Carpenter leads data strategy and AI at CenterSquare Investment Management.

Magic Moment

What’s the most fun or unexpected way you’ve used AI lately?

AI was unexpectedly impactful as a diagnostic safeguard. It analyzed molecular patterns to match tumors to cancer categories, valuable for unknown primary origin cancers.

An AI-driven molecular data analysis corrected a breast cancer misdiagnosis to B-cell lymphoma, changing treatment paths positively.

“Seeing AI as a safety net and decision-support tool highlighted its potential,” recounted a healthcare professional.