Tools & Platforms
Retail accelerates investments in generative AI
Dive Brief:
- Over half (56%) of retail organizations have upped their generative AI investments compared to last year, according to a report by Capgemini.
- Retail is among the top five industries most advanced in adopting AI agents, with 18% having implemented AI agents or multiagent systems, according to the report.
- Across industries, around 40% of organizations tracking ROI expect to achieve positive returns from AI within one to three years.
Dive Insight:
Generative AI has dominated the retail landscape with its various use cases from content creation to consumer-facing tools and more. As companies like Walmart and Target lean further on generative AI, the tech is making its mark in both how customers interact with retailers and behind-the-scenes workflows.
“Gen AI and agentic AI have unique capabilities, making them suitable for specific, non-overlapping tasks,” Sahil Chandratre, head of strategy, analytics and consumer insights for Reliance Retail, said in a statement. “For example, Gen AI is capable of addressing front-end tasks like customer communication and scheduling, and agentic AI is great at handling backend and complex activities such as billing and reconciliation. Systematically deploying the two in relevant areas can lead to synergies and streamlined workflows.”
When H&M introduced an AI-powered HR agent to streamline recruitment and candidate experience, it reduced time-to-hire by 43%, the report found. Additionally, employee attrition decreased by 25%.
Deploying different uses for AI is a balance Walmart and Amazon, among other companies, have attempted to strike.
Walmart’s generative AI shopping assistant Sparky, announced last month, can summarize reviews and help shoppers plan purchases. Amazon continues to push its own generative AI, including by introducing its next-generation Alexa+ assistant in February. Overall, shoppers are increasingly buying from generative AI’s product recommendations.
Meanwhile, companies like Visa and Mastercard are racing to create agentic AI tools that will perform as personal shopping assistants.
The shopping journey has become far more automated than some consumers may prefer. A recent KPMG report found that some shoppers may not fully trust AI or be comfortable with advanced shopping technology, like allowing AI to analyze personal customer data.
Tools & Platforms
State AI leaders gather at Princeton to consider how the technology can improve public services
Much of the news about artificial intelligence has focused on how it will change the private sector. But all around the country, public officials are experimenting with how AI can also transform the way governments provide essential services to citizens while avoiding pitfalls.
State AI leaders, including Gov. Phil Murphy of New Jersey, gathered at Princeton University in June to discuss how AI offers ways for government to be more efficient, effective, and transparent, especially at a time when budgets are strapped and economic uncertainty has slowed down hiring.
Hosted by Princeton’s Center for Information Technology (CITP), the NJ AI Hub, the State of New Jersey, the National Governors Association, the Center for Public Sector AI, GovLab, and InnovateUS, the conference brought together more than 100 AI leaders from 25 states to share ideas and collaborate. The meeting was conducted under an agreement of confidentiality to allow participants to discuss progress and concerns openly. Quotations in this story are used by permission.
What emerged was enthusiasm about AI’s potential to reduce the time government employees spend on manual tasks and improve their ability to engage citizens, as well as concerns about how best to use public data to innovate and increase equity rather than undermine it.
The gathering is just one of the ways that CITP – which is a joint center of the Princeton School of Public and International Affairs and Princeton Engineering – is leading on AI. The center also holds policy precepts to engage policymakers in AI governance at the SPIA in DC Center, and several affiliated faculty teach courses on AI policy at Princeton SPIA.
“There’s a clear recognition of the need for thinking about public accountability and equity,” said Princeton’s Arvind Narayanan. “At the same time, I think there’s also recognition of the potential for governments if we get this right.”
At the conference, CITP Director Arvind Narayanan noted that attendees were focused on practical implementation of AI tools rather than the “polarizing conversations around AI that dominate the media.” He also explained why public-facing deployments of AI by state governments have been slower than internal ones.
“There’s a clear recognition of the need for thinking about public accountability and equity. At the same time, I think there’s also recognition of the potential for governments if we get this right,” said Narayanan, who is also a professor of computer science and co-author of “AI Snake Oil: What Artificial Intelligence Can Do, What It Can’t, and How to Tell the Difference.”
Speakers shared big and small ways that AI is improving government. Some noted saving an hour or two a week per employee by leveraging AI to help draft grant applications, assess legislation, or review procurement policies while ensuring oversight and accuracy. One city automated the summarization of council oral votes, a task that was previously completed by a city clerk, creating summaries of 20 years of council books in a short period of time at nearly zero cost. As a result, voters have a simpler way to access information and hold elected officials accountable.
In his remarks, Gov. Phil Murphy laid out how New Jersey is approaching the technology, including its partnership with Princeton on the NJ AI hub.
“We held hands and jumped into the AI space,” Murphy said of the state’s partnership with the University. Together with Microsoft and New Jersey-based AI company CoreWeave, the state and University launched the NJ AI Hub earlier this year to foster AI innovation. “I don’t think we’d be all in if we didn’t think that the probabilities were very high that a lot of good things could go right with AI, but I think we also have to acknowledge some of the tensions that are still playing themselves out.”
Murphy highlighted concerns about AI’s potential to empower bad actors, as well as its impact on human creativity, jobs, and equity.
“Is this going to be something that is a huge wealth generator for the few, or are we going to be able to give access to this realm to everybody,” he said.
One of the ideas attendees considered at the conference was building a public AI infrastructure that would ensure it remains an open-source technology, rather than becoming privately controlled by a few companies. Bringing AI into the public domain would also present an opportunity to build in controls and mechanisms for accountability, speakers noted. They argued that AI is foundational infrastructure, not unlike roads, bridges, and broadband.
At the end of the two-day gathering, Anne-Marie Slaughter, chief executive of the New America Foundation and former Princeton SPIA dean, reflected on the conference. She emphasized what others had said about needing to be transparent in how AI is used and ensuring that public trust in government is strengthened.
“[AI] doesn’t just transform how government does things better, faster, cheaper. It can transform what government does and, even more importantly, what government in a democracy is,” Slaughter said. “You can start to co-create and you can start to co-govern.”
Posing with Gov. Phil Murphy at the conference are (left to right) Cassandra Madison of the Center for Public Sector AI, CITP Director Arvind Narayanan, New Jersey Chief AI Strategist Beth Simone Noveck, Timothy Blute of the National Governors Association and Jeffrey Oakman, senior strategic AI Hub project manager at Princeton.
Tools & Platforms
How Trump’s megabill could slow AI progress in US
The elimination of federal renewable energy tax credits in Trump’s One Big Beautiful Bill Act has major implications for the global AI race.
Ultimately, the shift means slowing down US progress on new energy production, which is key to winning the technology Cold War with China. There is no possible way tech companies can power the massive rollout of AI factories without solar, and now it will be that much more expensive.
But the attempt to throw a lifeline to the fossil fuel industry could be too little, too late, as detailed in this New Yorker article by Bill McKibben. The rate of solar adoption is now about a gigawatt every 15 hours. A gigawatt is the output of a typical nuclear power plant.
Solar isn’t just cheaper than fossil fuels. It’s also faster to deploy, which is crucial in the AI race. The expansion of AI data centers is creating new economic incentives for innovation in renewables, from geothermal to fusion to new battery chemistries, which can store all that new solar power. It’s a topic I expect we’ll be covering more and more here in the coming months.
Tools & Platforms
The AI Era Soft Skills to Prioritize for Career Growth
The Solutions Review and Insight Jam team has identified several soft skills that professionals throughout the enterprise technology market must prioritize in the AI era, according to proprietary research.
As artificial intelligence (AI) reshapes industries and transforms the nature of work itself, professionals face an unprecedented challenge: how to remain relevant and thrive in an increasingly automated world. While technical skills and AI literacy are undoubtedly important, the most successful professionals of the AI era will be those who master distinctly human capabilities that complement rather than compete with artificial intelligence.
The traditional career playbook gives way to a new paradigm where human insights fueled by adaptability and emotional intelligence become the primary drivers of professional success. Organizations are discovering that their most valuable employees aren’t necessarily those who can outperform AI at computational tasks, but those who can work alongside AI systems while bringing irreplaceable human judgment, creativity, and connection to their roles.
However, a proprietary study of over 200 senior tech professionals across markets and roles (you can check out the Solutions Review team’s research here) reveals a disconnect. While 94 percent of tech leaders agree that soft skills are more critical than ever, most admit their organizations lack the structure, time, or training mechanisms to develop them.
Findings like this should be a wake-up call for professionals, now more than ever. That’s why our team conducted the research in the first place and compiled some of the soft skills respondents identified as particularly valuable for the current market trends we’re seeing. Professionals prioritizing the five skills below will differentiate themselves from AI systems, enabling them to leverage AI tools more effectively, lead diverse teams through constant change, and create value that transcends what technology alone can provide.
5 AI Era Soft Skills Professionals Must Prioritize for Career Growth
Curiosity
In an era when information becomes obsolete faster than ever, curiosity has evolved from a “nice-to-have” trait to a career-critical capability. The half-life of skills continues to shrink as AI automates routine tasks and creates entirely new categories of work, which means professionals who maintain an active, systematic approach to learning and questioning will consistently outperform those who rely on static knowledge.
Our respondents agree, as 93.3 percent rate curiosity as “very” or “extremely important” to their careers. The problem is that nearly half of them also say they lack the time to commit to that learning. Curiosity in the AI era must go beyond passive learning, as professionals must actively seek an understanding of how AI systems work, where they excel, and crucially, where they fall short. The most successful professionals will be those who ask probing questions about AI outputs, challenge assumptions, explore the boundaries of what these systems can (and cannot) do, and identify opportunities for human-AI collaboration that others might miss.
Relationship-Building
The ability to build and maintain meaningful professional relationships has become more valuable, not less, especially with work becoming increasingly digital and AI-mediated. While AI can analyze communication patterns and even generate personalized messages, it cannot replicate the trust, empathy, and genuine connection that form the foundation of effective collaboration.
The complexity of modern organizations requires professionals who can navigate intricate networks of stakeholders, each with different priorities, communication styles, and levels of comfort with new technologies. While many tech professionals prefer working alone, despite recognizing the need for strong networks, 84.5 percent still acknowledge the importance of relationship-building. Once again, though, industry leaders say that prioritizing professional relationships is a struggle.
As AI democratizes access to information and tools, competitive advantages come from having access to diverse perspectives and early insights into emerging trends. The ability to cultivate relationships with thought leaders, potential collaborators, and industry pioneers becomes a significant differentiator.
Humility
Perhaps counterintuitively, humility has become one of the most powerful professional attributes in the AI era. As the pace of change accelerates and the complexity of challenges increases, the professionals who acknowledge the limits of their knowledge and actively seek input from others, including AI systems, often outperform those who rely solely on their existing expertise.
81 percent of tech leaders say humility (seeking and using feedback) is essential to their career success.
Intellectual humility manifests in several ways that can directly impact career growth. First, it enables professionals to embrace AI as a collaborator rather than a threat. Instead of viewing AI capabilities as diminishing their value, humble professionals recognize that these tools can amplify their effectiveness when used thoughtfully. They’re comfortable saying “I don’t know” and turning to AI systems for analysis, while also recognizing when human judgment is necessary to interpret and apply AI-generated insights.
This humility also extends to learning from failures and mistakes. In an environment where experimentation with new technologies and approaches is essential, the professionals who can quickly acknowledge when something isn’t working and pivot their approach are more likely to succeed than those who persist with failing strategies to protect their ego or reputation.
Resilience
Thanks to AI, technologies that once seemed permanent have become obsolete within years, entire job categories are disappearing as new ones emerge, and the skills required for success continue to evolve. In this context, resilience has become essential for long-term career success. Professionals and executives are well aware, too, with over 90 percent claiming resilience is a crucial skill, while also acknowledging that it can be challenging to recover from setbacks.
That’s why continuous learning remains essential. The more attention given to projects that promote resilience, the easier it will be for teams to acquire new skills, adapt to changing workflows, and maintain productivity during organizational transformation. Whether it’s an AI implementation that doesn’t deliver expected results or a skill that becomes automated, resilient professionals can bounce back quickly and extract valuable lessons from positive and negative experiences.
Perspective-Taking
According to survey findings, 84 percent of tech professionals value perspective-taking, yet 31 percent struggle to reconcile conflicting viewpoints. Further, an alarming 29 percent believe their perspective is the “best” one, even in teams with diverse views, which can become a major blocker to innovation.
Understanding and considering multiple viewpoints has become critical as AI systems reshape how work gets done and decisions are made. This ties into the importance of “humility” as a soft skill, as effective perspective-taking requires professionals to serve as interpreters between different stakeholders who may have vastly different comfort levels with AI and other assumptions about its capabilities. This skill proves particularly valuable when implementing AI solutions that affect diverse groups of users, customers, or colleagues.
The professionals who excel at perspective-taking often become the most trusted advisors and change leaders in their organizations, helping others see opportunities and navigate challenges that might otherwise seem overwhelming.
Conclusion
The AI era represents both an unprecedented opportunity and a significant challenge for professional development. While technical skills and AI literacy are important, the professionals who will thrive are those who develop distinctly human capabilities that complement rather than compete with artificial intelligence. The report shows that 94 percent of professionals agree that curiosity, resilience, and other critical soft skills are required for the future. And yet, most also state they lack the time, coaching, and feedback to improve these skills.
That lack of time is a problem, considering those soft skills are integral to successful business practices and professional development. For example:
- Curiosity drives continuous learning and innovation.
- Relationship-building creates the trust and networks necessary for effective collaboration.
- Humility enables productive partnerships with both AI systems and human colleagues.
- Resilience provides the foundation for adapting to constant change.
- Perspective-taking facilitates understanding across diverse viewpoints and technologies.
These soft skills work synergistically, reinforcing each other and creating a foundation for sustained career growth regardless of how AI continues to evolve. Promoting these soft skills requires support from the top down, and vice versa. Individuals should voice their desire for upskilling or ongoing learning programs, and executives must respond by providing them with the time and resources they need to focus on those skills. Doing so will create value that transcends what technology alone can provide and build careers that remain relevant and rewarding in an increasingly automated world.
The future belongs to those who can combine human wisdom with artificial intelligence, and these five soft skills provide the roadmap for making that combination both powerful and sustainable.
Take the Next Step: Help Shape the Future of AI-Ready Workforces
The best technologists of the future will not simply know how to build, prompt, or deploy AI. They’ll learn how to work with others, weather change, and see the bigger picture. Human-centered skills are the foundation of that future, and the time to start building them—systematically, strategically, and sincerely—is now.
To that end, the Solutions Review and Insight Jam teams are conducting a follow-up study to deepen our understanding of the human-AI skills gap, and we need your input.
Note: These insights were informed through web research and generative AI tools. Solutions Review editors use a multi-prompt approach and model overlay to optimize content for relevance and utility.
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