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When, just over a month ago, Donald Trump froze funding for the agency through which America doles out most of its aid, Mr Trump’s decision is an extreme example of a broader trend. On February 25th Sir Keir Starmer chopped Britain’s aid budget from 0.5% to 0.3% of gross national income to spend more on defence. France, the most generous Western donor after America, will this year reduce aid by 35%. Germany is considering cuts, too. Polling indicates broad domestic support for these decisions. Most big-name economists, including at the IMF and the World Bank, still insist on the importance of development spending—that intended to make countries richer—but even this consensus is fraying: some influential development economists now question how much good such spending really does. Could something better emerge from the mess?

But by halting USAID Mr Trump has also paralysed a much larger system dedicated to boosting economic growth. Development spending accounts for almost three-quarters of all aid. It most often subsidises favoured industries, frequently funds infrastructure construction and sometimes pays the salaries of teachers.

Development agencies were first established to support newly independent colonies. Inspired by the Marshall Plan, which rebuilt post-war Europe with American money, President John F. Kennedy set up USAID in 1961. The promise was that a richer world would be both better for the worst-off and friendlier to the countries financing its growth.

Things did not get going. From 2014 to 2024, the world’s 78 poorest economies grew more slowly than in the decade to 1970, when aid was first emerging. This is perhaps unsurprising, given earlier studies. In 2004 William Easterly of New York University and co-authors found that, from 1970 to 1997, aid was just as likely to shrink the world’s poorest economies as to help them grow. A year later the World Bank produced a post mortem on two decades of development aid, poring over the history of its recipients. The researchers concluded that its grants and loans did not move the needle on growth. In 2019 the IMF reached a similar conclusion.  Each generation of development spending has failed in its own way.  Health spending has had some real successes.

What lies behind this failure? Aid organisations are often criticised for wasting money on bureaucracy. In reality, they face a more fundamental problem: they have no idea how to encourage economic growth. The theory behind most Western aid has been staunchly liberal (in the British sense) for decades. Officials hope to build a private sector that can export to global markets, schools capable of furnishing firms with workers and infrastructure that will attract investment. Recipients are encouraged to dismantle regulation that stands in the way of free markets and to curtail unnecessary spending.

Yet it is hard to hand out enormous sums without turning poor countries into miniature command economies. Development projects mostly attempt to build entire industries, such as dairy farming or fisheries, from scratch. Disbursal conditions can have a faintly Soviet air.

Many problems are similar to those that plague industrial policy in rich countries, not least when picking winners. Western aid officials often want to prevent local politicians, who control crucial industries, from profiting as a result of their projects, meaning they select obscure sectors for tax breaks, credit and subsidies. With few investors willing to stump up capital, and little interest from local politicians, the businesses duly flop.

Recipient countries have created entire bureaucracies devoted to planning, securing and documenting aid.  This makes any cuts to development spending, no matter how inefficient, a nightmare. National leaders protest that they will have to reduce spending on clinics or schools, or resist loosening a currency peg. Indeed, adroit politicians must both work with donors, so as to keep services running, and dodge the difficult reforms they seek, so as not to upset voters. The governments of Egypt, Kenya and Pakistan all find themselves caught in this pattern, with politicians punished when they fail to keep both sides happy. 

Moreover, it is not just governments that are warped by aid. In many countries, everything from the banking system to import permits is designed to accommodate donors’ needs. Embryonic industries that are not favoured by aid officials barely stand a chance.

The next generation of aid is likely to be even more strategic, and less concerned with saving lives.

Imagine you run a meal prep company that teaches people how to make simple and delicious food. When someone asks ChatGPT for a recommendation for meal prep companies, yours is described as complicated and confusing. Why? Because the AI saw that in one of your ads there were chopped chives on the top of a bowl of food, and it determined that nobody is going to want to spend time chopping up chives.

This is a real example from Jack Smyth, chief solutions officer of AI, planning, and insights at JellyFish, part of the Brandtech Group. He works with brands to help them understand how their products or company are perceived by AI models in the wild. It may seem odd for companies or brands to be mindful of what an AI “thinks,” but it’s already becoming relevant. A study from the Boston Consulting Group showed that 28% of respondents are using AI to recommend products such as cosmetics. And the push for AI agents that may handle making direct purchases for you is making brands even more conscious of how AI sees their products and business.

The end results may be a supercharged version of search engine optimization (SEO) where making sure that you’re positively perceived by a large language model might become one of the most important things a brand can do.

Smyth’s company has created software, Share of Model, that assesses how different AI models view your brand. Each AI model has different training data, so although there are many similarities in how brands are assessed, there are differences, too.

For example, Meta’s Llama model may perceive your brand as exciting and reliable, whereas OpenAI’s ChatGPT may view it as exciting but not necessarily reliable. Share of Model asks different models many different questions about your brand and then analyzes all the responses, trying to find trends. “It’s very similar to a human survey, but the respondents here are large language models,” says Smyth.

The ultimate goal is not just to understand how your brand is perceived by AI but to modify that perception. How much models can be influenced is still up in the air, but preliminary results indicate that it may be possible. Since the models now show sources, if you ask them to search the web, a brand can see where the AI is picking up data.

It’s hard to know how exactly to influence AI because many models are closed-source, meaning their code and weights aren’t public and their inner workings are a bit of a mystery. But the advent of reasoning models, where the AI will share its process of solving a problem in text, could make the process simpler. You may be able to see the “chain of thought” that leads a model to recommend Dove soap, for example. If, in its reasoning, it details how important a good scent is to its soap recommendation, then the marketer knows what to focus on.

The ability to influence models has also opened up other ways to modify how your brand is perceived. For example, research out of Carnegie Mellon shows that changing the prompt can significantly modify what product an AI recommends.  Change from recommending a specific brand could range from 0% of the time to recommending it 100% of the time. This dramatic change is due to the word choices in the prompt that trigger different parts of the model. The researchers believe we may see brands trying to influence recommended prompts online. “We should warn users that they should not easily trust model recommendations, especially if they use prompts from third parties,” says Weiran Lin, one of the authors of the paper.

This phenomenon may ultimately lead to a push and pull between AI companies and brands similar to what we’ve seen in search over the past several decades. “It’s always a cat-and-mouse game,” says Smyth. “Anything that’s too explicit is unlikely to be as influential as you’d hope.”

Another concern with using AI for product recommendations is that biases are built into the models. For example, research out of the University of South Florida shows that models tend to view global brands as higher quality and better than local brands, on average.

AI can also serve as a focus group for brands. Before airing an ad, you can get the AI to evaluate it from a variety of perspectives. “You can specify the audience for your ad,” says Smyth.

Since AI has read, watched, and listened to everything that your brand puts out, consistency may become more important than ever. “Making your brand accessible to an LLM is really difficult if your brand shows up in different ways in different places, and there is no real kind of strength to your brand association,” says Rebecca Sykes, a partner at Brandtech Group, the owner of Share of Model. “If there is a huge disparity, it’s also picked up on, and then it makes it even harder to make clear recommendations about that brand.”

Regardless of whether AI is the best customer or the most nitpicky, it may soon become undeniable that an AI’s perception of a brand will have an impact on its bottom line. “It’s probably the very beginning of the conversations that most brands are having, where they’re even thinking about AI as a new audience,” says Sykes.

“Please come home to me as soon as possible, my love,” Daenerys Targaryen, Queen and Mother of Dragons, said to Sewell Setzer. Just an hour later, Sewell—a 14-year-old boy with kind eyes and curly brown hair, who loved sports, music, and spending time with his family—died by suicide, as reported in the New York Times. Sewell’s mother later uncovered that her son’s four-month relationship with “Daenerys” was facilitated by an AI-powered online companion, which he had created on the platform Character.AI. The company has since faced public outrage over its failure to detect and safely respond to the teenager’s distress.  

Digital well-being isn’t just about screen time anymore—it’s about how technology shapes our emotions, behaviors, and relationships. It’s about using technology in a way that supports our biological, psychological, and social health—fostering an intentional and balanced relationship with tech in both our personal and professional lives. Tragic incidents like Sewell’s highlight the urgency of understanding generative AI technologies (GenAI) and their impact on digital well-being. These new digital entities—whether called GenAI, chatbots, AI companions, or virtual agents—are not just tools; they’re forming real bonds with users, often in ways we don’t fully understand.

As psychiatrists, the authors have spent their careers helping people navigate complex relationships—with family, friends, pets, possessions, and now, digital entities. Patients are increasingly reporting emotional connections with AI characters, gaming personas, and online avatars. Just as social-emotional learning is vital for human relationships, understanding digital intimacy is becoming equally crucial.

At Brainstorm: The Stanford Lab for Mental Health Innovation, where we work to help companies build products that prioritize user health with responsibility and care, we developed the “Framework for Healthy AI” to guide industry best practices in AI product innovation.  This technology is still emerging, and we are all adapting to it in real-time as it evolves. The big question is: How can we help users cultivate healthy and safe digital relationships?

Given AI’s growing presence, individuals and communities must take charge of their digital interactions. The authors recommend discussing four key questions with friends and family to help assess and improve your relationship with AI agents.

4 questions to ask yourself:  What is your understanding of the AI agents you use?  How is AI affecting your time, both positively and negatively?  How is AI affecting your mental health and well-being?  What changes can you make now (include Set time limits, Use AI purposefully, Create AI-Freezone, and Discuss AI use?

AI will open doors for some workers while closing them for others.  Approximately 12% of U.S. workers are currently in occupations where gen AI is likely to automate away a significant proportion of the tasks associated with entry-level jobs. That, ineluctably, will lead to a reduction in entry-level hires. It’s already happening: With the advent of Microsoft’s gen AI–powered Copilot, hiring into entry-level software engineering jobs has largely stalled. Conversely, about 19% of workers are in fields where gen AI is likely to take on tasks that demand technical knowledge today, thereby opening up more opportunities to those without hard skills.

The authors’ analysis suggests that, in the next few years, the better part of 50 million jobs will be affected one way or the other. The extent of those changes will compel companies to reshape their organizational structures and rethink their talent-management strategies in profound ways. The implications will be far-reaching, not only for industries but also for individuals and society. Firms that respond adroitly will be best positioned to harness gen AI’s productivity-boosting potential while mitigating the risk posed by talent shortages.

With gen AI reshaping the landscape of work, businesses face a new reality that demands strategic adaptation. The parallel impact of raised and lowered barriers across different occupations will require a fundamental rethinking of organizational structures and talent strategies. Businesses will have to grapple, in particular, with the implications in the following areas.

1. Organizational structure.  New opportunities and challenges will emerge as gen AI reshapes organizational pyramids in some parts of the firm into more rectangular or diamond-like structures. Such structures may facilitate faster information exchange and more direct communication between organizational levels, allowing more agile decision-making and execution. They may also enable businesses to deploy smaller, more-agile teams.
2. Talent strategy.  Evolving organizational hierarchies will require companies to rethink how they handle recruitment and career development. Companies will probably focus recruiting efforts on fewer skills providers. Talent-acquisition teams will need to become significantly more agile to access talent pools that align with rapidly evolving technological demands.
3. Training models.  Once gen AI becomes widely integrated into the workplace, that will mean identifying and then investing in the skills that will be increasingly important to each role—and that keep those who are most experienced at the top of their game. Diamond-shaped organizations will need to restructure learning paths to facilitate the lateral transfer of experienced workers from other fields and workers whose careers may be disrupted by AI.
4. Company-specific knowledge.  As gen AI automates more-generalized skills, company-specific knowledge is likely to become an increasingly important factor in unlocking worker productivity. Companies will want to focus on identifying and cultivating this knowledge, and on whether and how to build infrastructure to make it more accessible to workers. This will involve decisions about the creation of new knowledge management systems, such as internal wikis and AI-powered learning platforms. Organizations will need to consider how much of a barrier they want company-specific knowledge to be and how to balance the benefits of specialization with the need for workforce flexibility.

In the theater of innovation, it is often the outsider who steals the spotlight.  Successful disrupters often start on the fringes, dismissed for their unconventional ideas or for pursuing paths others see as fruitless. But there is an upside to their outsider status: Unburdened by the ingrained norms and expectations that constrain insiders, they are uniquely positioned to connect disparate thoughts, see options that others have overlooked, and advance new perspectives that often have the potential of challenging, if not altering altogether, the status quo. Sociologists call this focused naivete — a productive ignorance of entrenched assumptions that enables outsiders to approach problems deemed trivial or unsolvable by experts.

Unfortunately, this freedom usually comes at a cost. The very distance that fuels outsiders’ innovative thinking can also hamper their quest for the backing and recognition needed to bring their ideas to fruition and share them with the world. Without traditional credentials, established networks, or experts’ stamp of approval, the outsider’s journey is often uphill.

Its a a broader paradox. As Paul Graham, the founder of Y Combinator, aptly observed, “Great new things often come from the margins, and yet the people who discover them are looked down on by everyone, including themselves.”1 This tension highlights the dual nature of outsider innovation: the ability to break free from conventional thinking while facing skepticism from those rooted in established norms.

How do successful outsiders navigate this paradox? More important, how can organizations remain open to the fresh perspectives that outsiders bring? The challenge lies not only in identifying original thinkers but also in empowering them — amplifying their voices, supporting their efforts, and fostering environments where atypical ideas can take root and thrive.  Successful companies look Outside, but Act Inside; fight Groupthink, and Find an Ally; Translate the Outside Into Inside Language; Nurture a Receptive Culture; and Ride the Inflection Points.

Workplaces are full of talented, educated, and hardworking women. Many are caught off guard when, several years into their careers, they see that they are falling behind their peers, and they can’t put a finger on exactly how or why.

Women, after all, are doing everything they can to prepare themselves for successful careers. As early as kindergarten, girls on average outperform boys across all disciplines, including math. Women in almost all developed countries earn undergraduate and graduate degrees at higher rates on average than men, with better grade point averages.

Yet quite quickly after graduation, many women start losing ground in the workplace. Despite making up 59 percent of college graduates in the United States, women represent only 48 percent of those entering the corporate workforce. And then come the first promotions to management roles: For every 100 men, only 81 women are promoted.

This advancement gap persists and compounds over women’s careers, with lower representation of women at every step of the corporate-leadership ladder. We call this phenomenon the “broken rung.”

The first broken rung of the corporate ladder opens up a gender gap that widens further at every subsequent rung, including senior-leadership positions. It is that first broken rung, however, that affects the entire talent pipeline. Despite initiatives to improve gender parity in the corporate ranks over the past decades, gains have been modest. The largest improvement has been in the C-suite, where women have moved from being one in five top executives to just over one in four reporting to the CEO. But 29 percent in the C-suite is still far from gender parity.

This disparity is not due to a lack of ambition. McKinsey’s Women in the Workplace report, conducted with LeanIn.Org, and other global surveys show that over the past decade, women have consistently shown a similar desire as men to be promoted and hold leadership positions.1 Seventy percent of men and women say they are interested in being promoted to the next level; the level of ambition to be a leader, be promoted, or hold the top job is even higher among women under 30 and women of color. Yet year after year, the data shows that this level of ambition does not come to fruition. Why?

After analyzing job profiles posted online across India, Germany, the United Kingdom, and the United States and using longitudinal data to trace actual career trajectories, we made an intriguing discovery. On average, for men and women, roughly half of their lifetime earnings come from the value they bring to the table when they start their careers, including their natural talents and formal education. The other half of their earnings stem from the value of the skills and experiences gained on the job, or what we call experience capital.

As we reviewed career trajectories of men and women in the United States, it became clear that women are not building the same levels of experience capital as men; they are not amassing the specific skills and experiences on the job that they need to be promoted at equal rates and to maximize their earning potential.

On average, for every ten years that a man is in the workforce, a woman is working for 8.6 years, given that women have the majority of part-time roles, formally work fewer hours, and take more frequent and longer leaves (typically to give birth or take care of children, or to take care of parents or in-laws). In addition, women are more likely to make occupational switches—accepting jobs that are more flexible or less competitive—that decrease their income quintile. Very little of the pay gap is because of initial jobs when men and women start out.

Although skills can be built without changing jobs, they are developed and recognized the most when an individual is promoted to a new role. And so the gender gap in job moves or promotions is a long-hidden driver of the gap between women’s and men’s incomes over the course of their careers.

Companies can take important steps to fix the broken rung by making sure employees are getting equal opportunities for leadership and promotion. But waiting for companies to change is not a strategy. In the meantime, women can take individual action to build their own experience capital.  To start with understand that job change is a constant, research occupations that present opportunities, consider brand-new jobs, turn yourself into a technologist, escape a shrinking industry, explore industries with growth potential, and consider moving to where the jobs are.

Amid economic pressures, rapid developments in AI technology and other broader changes in the media landscape, many companies are downsizing or restructuring their communications departments. The trend of consolidating and refining comms functions means fewer opportunities and stiffer competition for all professionals in the field—even the most experienced and successful among them.

In such a climate, standing out requires not only experience, but also a proactive approach to highlighting the value one’s proven aptitude and deep expertise bring to the table. 16 Forbes Agency Council members offer key steps to take to ensure sustained relevance and continued career growth in a fast-paced, ever-evolving space.

1. Prioritize Continuous Learning.  Experienced communications professionals should prioritize continuous learning. One effective step they can take is to invest time in developing their skills in digital communication strategies, social media engagement and analytics. Analytical tools and understanding audience KPIs can help refine messaging and strategies to meet the changing needs of the audience.
2. Blend New Tech With Strong Storytelling.  As an experienced professional, staying relevant means constantly evolving with the times. Embracing new tech and tools, like AI, for streamlining processes and amplifying messaging is key. But the real game-changer is blending that tech with strong storytelling and authentic connections, because no matter how much things change, people still crave genuine communication.
3. Expand Your Expertise; Develop Your Unique Style.  Remain authentic and expand your expertise. We constantly hear about the significance of authenticity, but not everyone fully realizes how big of a role it can play. Work on a unique tone of voice and make it distinct; avoid formalizing your language and your writing style. As a content creator, you must be an expert in your focus field.
4. Translate Trends Into Real-World Impact. Client education is key. AI is powerful, but it can’t replace strategic human insight. Experienced pros must focus on educating clients on the nuances of effective communication, helping them navigate complexity, refine messaging and adapt to change. Staying relevant means being the expert who translates trends into real-world impact, not just tactical execution.
5. Share A Variety Of Info With Internal Audiences.  Consider sharing alternative information sources with your internal audience and (especially) executive team. This can include not only insightful reviews or social media posts, but also results of customer engagements, such as surveys, net promoter scores or (most importantly) results from your customer advisory board meetings, where unique and valuable insights were no doubt acquired.
6. Embrace Adaptability; Deepen Digital Literacy.  Experienced communicators should embrace adaptability and deepen their digital literacy. As media evolves, mastering new tools, platforms and data-driven strategies is crucial. Staying ahead means blending traditional storytelling with innovative tech—being able to pivot seamlessly between channels while keeping human connection at the heart of the message.

The others are:

Track Interests To Personalize Messaging

Integrate AI Efficiency With Human Skills

Identify And Capitalize On Story Opportunities

Become The Go-To Strategist

Build Your Data Analysis Skills

Embrace Data-Driven Storytelling

Become An AI Communication Specialist

Go Back To Primary Agency Principles

Understand The Internal Audience

Upskill And Foster Strong Internal Networks

To put together a best-in-class list of America’s top 500 female founders, Inc. rounded up a crew of the greats.  These women know what it takes to perform at the highest levels of business.This year’s Female Founders advisory board members share their best advice for starting and growing a company now.

1. Pace Yourself.  This is a marathon, not a sprint. It’s important you define your own goals and metrics for success, as a founder and a business. Run your own race and stay in your lane.
2. Take Care.  Become an expert in both supporting and investing in yourself, so you can consistently operate at the level of excellence required to do great things.
3. Embrace Failure.  True success comes not from avoiding failure, but from turning your setbacks into stepping stones. Don’t let fear or doubt stop you. Your determination and resilience can transform challenges into generational wealth and lasting impact.
4. Listen to Your Customers.  Your customer base should always serve as your north star, guiding your decision-making. Flexibility doesn’t mean abandoning your vision; it means evolving it to create a product or service that truly resonates.
5. Understand the Economics.  It’s easy to get caught up in the passion of an idea, but for it to be a great investment—of your time and others’ money—it must have the potential to scale and generate returns. That means building not only a business with a strong economic foundation, but also one that solves a pain point your customers face daily or weekly—something they truly can’t live without.
6. Build Your Community.  Entrepreneurship is not a solo journey. There is no challenge you will encounter that someone else has not faced before. Instead of asking yourself, ‘What am I going to do about this? How can I solve this?’ ask, ‘Who can help me solve this?’ Lean on your community—this support system will accelerate solutions and, ultimately, your business growth.
7. Trust Your Team.  Real leaders give permission to their teams to own their responsibility and have the opportunity to explore and take some risks.

In e-commerce, startups often focus on typical trust signals, such as customer reviews and security badges (SSL certificates), to convey to potential customers that they can be trusted — but in a crowded market, this alone won’t suffice.

There are some uncommon trust signals startups can leverage.  

1. A big number associated with your customers/products:  If you are a startup that has sold to a significant number of customers, do not hesitate to publicly disclose this figure.  Perhaps you haven’t yet sold to 100,000 customers and consequently don’t want to display the number of customers. You can be more creative in such cases and focus on, perhaps, the number of units you have sold; this can be interesting if each product you sell comes with multiple units. For instance, if you sell pairs of socks that come in packs of five, then instead of counting 20,000 orders, you can signal that you have put 100,000 actual pairs of socks on people’s feet. If you sell a liquid product, maybe the volume sold is more interesting than the number of customers. Your creativity is your best friend in this context.
2. Real-time statistics.  Showing real-time statistics (like the number of customers who have viewed a website) is more common; however, you can still leverage this principle of showing real-time data with more creative numbers. Maybe you’re a coffee roaster who has sold 2,437 bags this month — why not show this in real-time on your product pages? This will help customers see active engagement, reinforcing that your business is active, thriving and in demand.  Another metric you can utilize in such a context is a zip code tracker.

Integrate trust signals into product messaging.  Once you have identified the specific metrics that will help your customers trust your brand and product, you should leverage these metrics across multiple surfaces and customer touchpoints.  Besides product pages, a few other critical touchpoints are checkout pages, post-purchase pages/emails and your newsletters. Take every opportunity to highlight your key trust metrics.

Pitfalls and best practices.  Firstly, it is important that you do not fabricate any statistics. This is a surefire way to ruin your reputation if discovered. This will also not help you build the right culture amongst your employees.  Another aspect to remember is to not overload your customers with too many statistics. Be clear about the one or two key figures that you feel will move the needle and only publicize those.  Lastly, if possible, communicate these trust signals with humor, but don’t undermine your credibility with overly gimmicky tactics.