Is AI just giving customers more to ignore?
Editor's note: This is AI Impact, Newsweek's weekly newsletter where each week, we will explore how business leaders are unlocking real value through artificial intelligence.
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Good morning and thanks for joining me.
I've spent the past few weeks reporting on what companies have to figure out after they give people access to AI.
According to KPMG, the issue is proficiency : lots of people are using the technology, but very few are applying it in sophisticated ways across their work. My conversation with FICO followed the output from AI into real business decisions. When a model begins affecting a customer, the company needs to know how that decision was reached and be able to explain it.
Today, I'm looking at what happens when AI starts shaping the customer experience.
Marketing makes that especially visible. People open, click, buy, stick around or tune out, giving companies signals they can use to judge whether the technology is improving the experience.
In this week's Signal Capture, we'll get into how marketers can measure whether automation is improving customer outcomes, what small and midsize businesses may understand about adoption that larger companies overcomplicate and where people still need to guide the system.
I hope you have a wonderful holiday weekend, and I'll catch you next week.
Signal Capture
Signals from the frontlines of AI adoption
ActiveCampaign CEO: AI Speed Means Little If Customers Tune Out
Producing more marketing content faster can create its own problem: The volume can rise without improving engagement, conversion or retention.
Jason VandeBoom, CEO and founder of ActiveCampaign, an autonomous marketing platform, said the volume of material a team can produce is a poor measure of whether AI is creating value.
"AI speeds up creation, but this does not automatically mean increasing customer value," VandeBoom told Newsweek . "Businesses can deliver more content and more communication to potential customers, but risk creating 'AI slop' that saturates audiences with low-quality marketing."
The better test, he said, is what happens after that material reaches customers. Companies can look at satisfaction, response quality and lifetime value, along with whether people act on the marketing and remain customers, to determine whether AI is improving customer outcomes rather than simply increasing output.
VandeBoom said the way AI is built into a product matters, too.
"If you're still doing the same work with a chatbot layered on top, the impact on a marketing workflow will be incremental, and unlikely to create substantial value," he said.
The most effective AI is embedded in a workflow and grounded in a company's own data, historical performance and real-time signals, according to VandeBoom. In marketing, that could mean spotting a change in audience behavior, identifying an opportunity, recommending who to target and what message to use, then adjusting the campaign based on performance.
The difference, he said, is that the system can do this without waiting for a marketer to ask what to do next.
As those systems take on more initiative, marketers also need to understand why they are recommending an action.
An automated system recommending or changing a campaign should provide the signals behind its recommendation, the objective it is optimizing for, the trade-offs it considered and the effect it expects the action to have, VandeBoom said.
"Automation should increase marketer confidence, not diminish their ability to guide outcomes," he said.
Clear guardrails and the ability to intervene or provide feedback remain important even when the system handles more of the execution, according to VandeBoom. Marketers should be able to steer the outcome without having to manage every decision manually.
ActiveCampaign is also looking at what real user conversations with AI reveal about whether those systems are working. The company acquired Feedback Intelligence, an AI evaluation and analytics tool, to analyze interactions and identify whether an AI system is answering accurately and resolving the problems users bring to it.
"Measuring actual interactions helps businesses improve models so they don't exist in a vacuum," VandeBoom said.
Small and midsize businesses tend to start with immediate problems: work consuming too much time, bottlenecks or customer communications falling short, VandeBoom said. Larger organizations, by contrast, can spend more time assessing AI adoption across teams.
The questions, he said, are straightforward: "Will this save time? Will customers have better experiences? Will it help the business grow?"
VandeBoom sees AI taking on more of the analysis behind audience segmentation and campaign optimization as it learns from large amounts of marketing data. Marketers can remain responsible for strategy, setting brand direction and deciding when to intervene.
Companies that make AI useful will measure customer outcomes closely and keep improving based on real-world feedback rather than judging success by how many AI features they add or how much content they produce, VandeBoom said.
"Customers ultimately care about better experiences, not the technology behind them," he said.
Upcoming Webinars
Overcoming Barriers to AI Transformation in Legacy Industries
AI investment is accelerating, and long-established companies are finding ways to bring the technology into organizations shaped by years of customer relationships, complex operations, critical systems and regulatory responsibilities. The challenge is turning promising pilots into lasting business results without disrupting the strengths that have made those companies successful.
In an upcoming Newsweek AI webinar presented by Cognizant, Gabriel Snyder, Newsweek's executive editor, enterprise, will moderate a discussion titled " Overcoming Barriers to AI Transformation in Legacy Industries." The conversation will delve into how established organizations are connecting AI to existing systems and workflows, clarifying ownership and governance and aligning technology investments with people, processes and measurable business outcomes.
Matt Sanchez, chief operating officer at Yahoo, Durga Malladi, executive vice president and general manager of technology planning, edge solutions and data center at Qualcomm and Katy George, corporate vice president of workforce transformation at Microsoft, will join the conversation.
Join the live discussion on October 21. Register for free .
The Inflection Point: How Agentic Operations Compound Enterprise Value
The next phase of enterprise automation is moving beyond tools that assist employees and toward systems that can execute parts of a business process themselves. That raises bigger questions for leaders about where people remain accountable, how operating models need to change and what happens to the economics of work when machines take on more of the execution.
On September 17, Dr. Ranjit Tinaikar, host of Newsweek's "AI Impact Forum," will sit down with Balkrishan "BK" Kalra, president and CEO of Genpact, for "The Inflection Point: How Agentic Operations Compound Enterprise Value."
Kalra will bring Genpact's perspective on what it calls "Agentic Operations," including lessons from its own implementation and research into why some enterprise investments produce value while others stall.
They'll get into the implications for jobs and roles, responsible AI controls, operating models and commercial structures as companies give autonomous systems a larger role in how work gets done.
Join the live discussion on September 17. Register for Free .
Prompt Injection
What's one recent insight you've learned about AI?
Sudhir Chaturvedi | Global Chief Growth Officer and North America CEO, NTT DATA
"One of the biggest insights I've had about AI is that technology is rarely the constraint. Most organizations can identify compelling AI use cases. The harder challenge is whether their infrastructure, data environment, operating model, and workforce are ready to support AI at scale.
Early on, many companies approached AI by launching initiatives across every part of the business. What we're seeing now is a shift toward focus. Leaders are realizing that concentrating on a small number of high-impact opportunities delivers far greater value than pursuing dozens of experiments with unclear outcomes.
That realization has changed how I think about AI adoption. Success isn't just about deploying models, it's about aligning people, processes, technology, and data around a clear business objective. When organizations focus on the areas that matter most and invest in the foundations needed to support them, AI moves from a promising pilot to a true driver of business transformation."
Have your own lesson to share? Email us at: [email protected]
Run Log
AI use case of the week
Datavant's AI Speeds the Search for Drug-Development Data
Before researchers can use real-world data to guide a drug-development decision, they first have to find the right data, a search that can take months or even years.
Sara Livengood, senior vice president of product management for life sciences at Datavant, a health data company, said finding the right data can become a bottleneck during clinical development. Real-world data is information captured during routine patient care.
Datavant built Explore Assistant, an AI tool for finding and evaluating real-world health data, so researchers can search complex datasets with ordinary-language questions instead of writing database queries or contacting data providers individually.
Large language models convert those questions into structured searches, while metadata about the datasets helps researchers determine which ones fit a study. Datavant pairs the AI with scientific expertise, evaluation frameworks and human oversight to check the recommendations.
In one oncology engagement, Livengood said a pharmaceutical company used Explore Assistant to identify the real-world data it needed in one week, down from about two months.
The company is also applying AI to other parts of the study lifecycle, including developing clinical definitions, writing protocols and disseminating results.
"Any time saved to better understand safety and efficacy of certain therapies is extremely valuable," Livengood said.
Have an interesting AI use case to share with us? Email us at: [email protected]
Context Window
â– Nvidia agreed to acquire Hugging Face for $12.93 billion, while pledging that the platform will remain open to models, clouds, inference providers and computing platforms beyond Nvidia's own ecosystem. [ Nvidia ]
â– BCG argues that AI can cut IT modernization costs by 25 to 35 percent and accelerate implementation by 30 to 40 percent, but only when companies match different AI tools to specific tasks, supply sufficient system context and maintain engineering guardrails. [ BCG ]
â– MIT researchers studying AI adoption at more than 20 companies found that effective deployments require evidence before scaling, calibrated worker trust and continued investment in learning, teamwork and domain expertise. [ MIT Sloan ]
â– OpenAI says its upcoming Astra model is the first to meet its "Critical" cybersecurity capability threshold, able with the right tools and access to find unknown vulnerabilities and develop exploits across hardened systems, prompting stronger safeguards and limits on its most advanced cyber capabilities. [ OpenAI ]
â– Several major law firms are building or customizing their own AI systems for complex and commercially sensitive work as they seek to differentiate their services and protect proprietary expertise. [ Financial Times ]
Transfer Protocol
Tracking executive moves across the AI landscape
Priya Vijayarajendran, former CEO and board member at ASAPP, has joined Genpact as chief product and platform officer, leading its move toward productized, IP-led agentic solutions and scaling data, AI and agentic operations across clients.
Nick Marzotto, who led clinical applications and artificial intelligence at Epic, has joined PartsSource as vice president of AI and data, directing its AI strategy and expanding AI, machine learning and intelligent automation across its clinical technology platform.
John Renaldi, after VP and GM roles at Google and Motorola, has been appointed chief AI officer at Leelyn Smith, building infrastructure to connect client information across the firm's wealth management, tax and financial planning operations.
Tom Bonos, coming from chief operating officer and chief revenue officer roles at Applause, is Sumo Logic's new chief revenue officer, leading global sales and customer success as customers deploy agentic AI across security and cloud operations.
Daniel Sogorka, whose lending technology career includes senior roles at Black Knight/ICE, ServiceLink/FNF, Sagent and Rocket Pro, has been named CEO of Informed, scaling its AI-powered fraud protection business and expanding into adjacent lending markets.
Olya Ossipovahas been named chief product officer and Datong Sunvice president of engineering at Hume AI, strengthening the New York-based company's leadership as it develops data and infrastructure for improving and aligning voice models with human emotion and expression.
Know someone on the move in AI? Send job change info to [email protected]
Magic Moment
What's the most fun or unexpected way you've used AI lately?
Jaclyn Wands | VP of Product and AI, Phaedon
"AI isn't always about work and productivity. I have been using AI to rebuild my own story.
We are all moving fast into the future and I did not want to lose the part of me that came from somewhere. I started dropping fragments of my memory and past experiences into a running file whenever one surfaces. A specific afternoon from when I was seven. The exact phrasing of something my grandmother used to say. A smell, a car, an argument, a joke nobody outside my friends would understand. Most of them arrive at useless moments, in an airport or halfway through a meeting, and before this they evaporated. Now they get caught.
I plug them into my AI working book, using key memories as time boxes so that the AI can organize my thoughts into a coherent timeline. My AI assistant holds the pieces of stories, asks me questions to pull the rest of one out, and keeps track of what I have already told it. My story is constantly being built. What I want out of it eventually is an illustrated book of my own small adventures, using AI to animate the story, something that includes my life lessons, is tangible, and gives me something I can read to my kids.
My job is helping brands maintain their highest value relationships in the age of AI. I turned that method on myself. The most valuable tool I have built this year reflects the most meaningful relationships in my life."
Experience some AI magic? Tell us about it at [email protected]
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