Citizens for Judicial Fairness Slams Excessive Delaware Chancery Fees Following New Stanford Report
The findings were highlighted in The New York Times' DealBook newsletter, and arrive as more companies continue to question Delaware's value as the 'gold standard' for corporate law.
Citizens for Judicial Fairness released the following statement in response to the study:
'This study confirms what we've been saying for years: Delaware's Chancery Court is more interested in enriching lawyers than serving shareholders or protecting everyday investors. Two judges, Chancellor Kathaleen McCormick and Vice Chancellor Travis Laster, are responsible for a majority of these outrageous fee awards, and must be reined in so that litigants in Delaware's courts can have reasonable fee expectations. The pattern is clear: corporate insiders and well-connected firms are cashing in while Delaware's reputation burns. Delaware lawmakers can't look the other way anymore. These payouts aren't normal, and they aren't defensible. They're part of a system that's increasingly out of step with every other court in America. It's time for serious reform – and if Delaware won't fix it, the market will.'
The Stanford paper shows that two judges alone account for over 60% of the supersized awards, which often exceed ten times the base legal fee. In some cases, lawyers were paid nearly $50,000 an hour after inflation adjustment. No federal judge has ever come close to authorizing these kinds of fees.
Citizens for Judicial Fairness has long advocated for transparency, common-sense reform, and balance in the state's corporate legal system, and has warned that if left unchecked, judicial overreach will drive companies, jobs, and corporate revenue out of Delaware.
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Forbes
2 days ago
- Forbes
Stare Decisis To Foresight: A Legal Mindset For The AI-Era World
Gear symbols on the head shape. Antonyms. We live in an age of constant, accelerating, and converging change. It is challenging human capacity to adapt--a 21st century edition of 'Future Shock.' That applies equally to individuals and organizations. What separates those that adapt to change and see it as an opportunity from others who are overwhelmed by it and mired in stasis? Mindset is a key factor. It is the prism through which human behavior is filtered. Mindset influences decision making, risk tolerance, curiosity, collaboration, learning, and other important life and career influencers. Carol Dweck, a Stanford University psychologist, divided mindset into two distinct camps in Mindset: The New Psychology of Success. A fixed mindset, according to Dweck, sees capabilities and conditions as static, prioritizing risk avoidance and stability over creativity and exploration. A growth mindset, in contrast, embraces learning, experimentation, and the pursuit of improvement. Despite the controversy around its findings, it is still useful to see mindset in two categories with the caveat that each has gradations. Mindset matters now more than ever. In a real-time, AI-enabled business environment marked by speed, complexity, interconnected risk, and uncertainty, a flexible, forward-thinking mindset has become a requisite to navigate change. Responsible, informed, and creative deployment of AI, data, and other tools is an important element of a growth mindset. So too is developing what Accenture calls a 'digital core' (data, AI, and cloud competency). Teamwork, a shared sense of purpose, curiosity, constant learning, informed experimentation, and a culture that values and supports these attributes, are additional characteristics of a forward-thinking mindset. Research has shown that alignment of mindsets—whether in personal relationships or business—is linked to better outcomes. John Gottman, an American psychologist known for his data-based studies on divorce prediction and marital stability, found that couples who create 'shared meaning'—a common vision of goals and values—are far less likely to divorce. Similarly, research on relational 'growth mindsets' reveals that people who believe relationships can improve with work tend to handle conflict better and maintain higher relationship satisfaction over time. Business offers strikingly parallel findings. Companies that align their mindset and culture around learning, experimentation, and shared vision consistently outperform less adaptive competitors. McKinsey research found that agile organizations deliver ~40% higher total shareholder returns over five years compared to their peers A BCG study revealed that companies with strong adaptive cultures are nearly twice as likely to succeed in digital transformations. Multiple studies have shown that alignment of mindset is a fundamental driver of long-term success. Law and business have divergent mindsets. The 'mindset gap' separating them has widened dramatically during the past quarter century. The divergence is a tale of different responses to a rapidly changing business, geopolitical, and macroeconomic environment. Business has adapted a growth mindset; the legal industry has remained rooted in its fixed mindset and culture. The 'mindset gap' separating law and business adversely impacts not only the legal industry but also business, and society. It diminishes the legal function's efficacy and dilutes its potential enterprise value by narrowing legal's sphere of influence to 'legal' matters rather than expanding its imprint across the many business units law intersects with. It also undercuts enterprise transformation by failing to leverage legal's strategic and problem-solving capabilities and institutional knowledge to create business value. Perhaps most importantly, law's mindset gap has deprived society of an accessible, affordable, fit-for-purpose legal function. This has produced an erosion of public trust in the legal profession, its institutions, the rule of law, and democracy. That negatively impacts commerce, the economy, business, commercial transactions, judicial resolution of disputes, and human rights. What are the causes of the business-law mindset gap, and how can their divergence be bridged to create a legal function that better serves business and society in an AI-enabled world? These important questions have received insufficient attention, perhaps because they principally involve the human side of transformation more than technology. Paradoxically, rapid technological advances—notably AI—have elevated, not marginalized, human qualities that separate us from machines. Soft 'skills (empathy, curiosity, creativity, teamwork) have long been undervalued by the fixed mindset and culture of the legal industry. A spate of psychological studies have found that soft skills are much harder to teach than technical or procedural ones. The takeaway is that for many in the current legal workforce, the transition to a team and customer-oriented mindset will be difficult. EY conducted a study that revealed more than 50% of GC's surveyed reported that legal culture and resistance to change is the greatest obstacle to modernization. Thomson Reuters conducted a similar study that echoed the EY findings, concluding that culture and change resistance eclipse budget and technology gaps as the principal change retardants. The transformation of business during the past quarter century is the story line of the mindset gap with law. This column has long maintained that legal transformation is a business story. Business, especially industry leaders, are well down the path of the transformation journey. The legal function—excepting an expanding number of in-house teams—is just beginning. Business has created a blueprint for legal transformation. It starts with mindset and culture. The Business Mindset Transformation Until the turn of the Millenium, most businesses had a fixed mindset. It was rooted in tradition and past practice, relying on proven models, standard operating procedure, and industry best practices to reduce risk and promote consistency. Adaptation usually took a back seat to stability in a world where change occurred more gradually, the speed of business (and life) was considerably slower, and technology had not yet created what author/journalist Tom Friedman described as a flat world. As Lou Reed noted in a different context, 'those were different times.' The last quarter century has exposed the limitations of a fixed mindset in a rapidly changing world and marketplace. Business has confronted a constant, escalating array of interconnected challenges. A sampling includes: rapid technological advances industry disruptors and asymmetrical competition transitioning from an analog to a digital world (digital transformation) globalization- then its collision with nationalism 9/11 the global economic crisis Covid-19 social media state-sponsored armed conflicts, terrorist attacks, domestic terrorism, etc cyber breaches geopolitical and geoeconomic shifts polarization (social, economic, and political) climate change mass migration data explosion artificial intelligence (its challenges and opportunities). Business recognized these interconnected challenges posed an existential threat, one that could not be extinguished-- much less turned into opportunity--by a fixed mindset and strict adherence to what had worked in the past. This spelled the end to 'business as usual.' Mindset and cultural shifts do not come quickly or easily, nor can they be effected by fiat. The journey begins with leadership providing a clearly articulated strategy that explains the 'why' of transformation. It is systematically reinforced until there is widespread buy-in across the enterprise. Transformation is a team sport, one that requires shared purpose, goals, and an ethos that 'the whole is greater than the sum of its parts.' The transition to a more humane mindset and culture requires tough human decisions; not everyone in the workforce can or will adapt, even when afforded the opportunity and tools to do starts with human adaptation, not with technology. The latter creates opportunities to change and seize opportunity by creating new business structures, economic models, and ways to elevate customer outcomes and experience. The workforce—and that includes the business's supply chain and strategic partners-- determines the success of the adaptation journey by its willingness and ability to adapt. Only then can technology be creatively, responsibly, and usefully applied to internal reorganization that produces better customer outcomes and experience. Fostering a growth mindset is key to individual and collective success. Top performing businesses recognized early on that investment in the workforce—upskilling, purpose, collaboration, etc.—is an essential component of successful transformation. Reimagining talent in a rapidly changing environment is critical, and so too is investment in upskilling and cultural reformation. Google, for example, launched Project Aristotle, a research initiative focused on what makes teams effective. The study analyzed data from hundreds of teams over several years. It concluded that psychological safety was the crucial element of team success. This underscores the importance of humanity in the transformation journey. Microsoft provides another example how mindset and culture can drive success. When Satya Nadella became the tech giant's CEO in 2014, the company was in a trough. Nadella championed a growth mindset and cultural shift focused on learning, collaboration, and cloud-first innovation. This gradually replaced the siloed, internally combative culture that Nadella inherited. The mindset and cultural shift paid off; it produced a dramatic turnaround in Microsoft's market value and brand, a trajectory that continues more than a decade later. Mindset and culture are closely connected. Culture is forged by aligned mindsets that share, reinforce, and institutionalize their values, practices, and goals across the group. Culture is an amalgam of how a group identifies itself and what it stands for. Social cohesion and progress are largely determined by how widely a unified mindset is achieved. Leadership's ability to forge a culture of shared understanding, purpose, teamwork, and goals is critical. This--like other human elements of transformation-- is especially true during periods of rapid, interconnected change. A growth mindset supports a holistic, proactive approach to risk management and uncertainty. Risk can be managed, because, to channel Peter Drucker, it can be measured. Uncertainty, however, cannot be measured, and--like risk-- there is a great deal of it in the current business environment. Top performing companies have embraced and invested in foresight to anticipate and prepare for uncertainty. Foresight includes identifying signals that portend change, scenarios planning, and critical thinking applied to 'connecting the dots,' among other types of horizon scanning. Scenarios planning is not new; Shell pioneered it back in the 1970's. The foresight tools that can now be applied--predictive analytics, scenario AI-driven forecasting, and the like have become more powerful, enabling businesses that use them effectively not only to anticipate change but also to turn it into strategic advantage. Those tools are also available to competitors; mindsets and cultures are key factors in what separates leaders from laggards. Data supports the marked divergence of enterprise mindset and culture separating companies that fail from those that succeed. WatchMyCompetitor, an AI-powered competitive intelligence platform, conducted research on why companies decline. It reported more than half (52%) of the companies in the Fortune 500 list in 2003 no longer exist today, and 72% of the original 1984 FTSE 100 companies are now gone. The takeaway is clear: in today's world, business must adapt or confront obsolescence. The study identified six common reasons for corporate decline: All six failure elements relate to mindset and culture. Technology accelerates and enables change. Human adaptation—a growth mindset, forward thinking culture, and aligned, agile, fluid, team-oriented, integrated, and creatively curious workforce seizes opportunity from change. Law's Retrospective Mindset and Culture The legal profession/industry has a deeply rooted, fixed mindset. It is embodied by stare decisis, a legal principle of judicial adherence to past decisions. The rationale is to promote stability, consistency, and fairness. Law's mindset, culture, criteria for guild admission, pedagogy, hierarchical organizational structure, pyramidal economic model, pedagogy, and linear career trajectory evidence its adherence to the past. Legal language (a/k/a 'legalese') is abstruse and chock full of Latin terms, evocative of its strong ancestral ties. The legal guild constructed a language designed for itself, thereby separating lawyers from 'non-lawyers. This purposeful distancing from clients and society-at-large is emblematic of the myth of legal exceptionalism as well as the reality of legal insularity and separatism. Law's anachronistic rituals-- court proceedings where judges sit on elevated platforms, gowns, wigs, and other symbols of pomp and ceremony, are not intended to be inviting or to put 'outsiders' at ease. Law is a people and persuasion business, but everything about it creates the opposite effect for non-guild members. Legal culture has rewarded cultural compliance, risk-aversion, and an artisanal approach to problem solving-- no matter its correlation to client value. The legal profession has offered lip service to 'partnering with clients,' 'cutting edge technology,' and 'investing in our most important asset, our people.' This is belied by high turnover (especially law firms), client dissatisfaction, the migration of work from law firms to in-house corporate teams, and law's ambivalent embrace and negligible investment in technology and training. Law schools, likewise, retain a fixed mindset. Their doctrinal emphasis, siloed study of core subjects (rather than an integrated approach that reflects the realities of practice), elevation of issue identification over problem solving, and faculties thin on practice experience and/or marketplace awareness are out-of-synch with the evolving role and purpose of the legal function in a rapidly changing marketplace. Legal education is about rote learning and spotting issues, not understanding concepts, drawing connections, and creatively applying them to problem solving. Customer/client relationship building, the service component of legal delivery, and a multidisciplinary approach to problem solving are also lacking in law schools. The traditional law firm partnership structure and hierarchical, labor-intensive economic model have survived and thrived for generations. Firms have prospered as business has consolidated, grown, and transformed. Regulation and compliance has become more onerous and complex, litigation (particularly in the US) has continued its upward spend trajectory, business has faced new risks and greater uncertainty, and technology has spun off new practice areas. The global legal services market was $300B in 2000; it is currently estimated at $1T. Partner profits, especially among twenty or so 'elite' firms that handle the lion's share of high value M&A and litigation work, are at an all-time high. So too are firm rates, margins, and partner profits far outpacing the broader economy. Their corporate clients have transformed, but law firms have been under little pressure to do the same. Why, then, are so many legal leaders so concerned about the future? Spoiler alert: business has already quietly begun to transform the legal function from within, focusing on reimaging the in-house legal function. Concurrently, AI is poised to accelerate that process and deliver the coup de gras to the law firm partnership model. That will transform the legacy delivery paradigm by eliminating the economic friction between corporate legal teams and firms. It will also accelerate the creation of new AI-first corporate provider sources that can 'productize'—and customize— faster, better, cheaper' legal products and services at scale. Those products and services will extend beyond the narrow parameters of 'legal' issues and include risk management, regulatory and compliance, IP, cybersecurity, corporate governance, etc. Business has been conducting a skunk-works transformation of its in-house legal teams for years. It is changing the corporate legal team's role, remit, metrics, composition, and talent mix. The goals are not only to save on outside legal spend, but also to extract the latent potential of legal to create value for the enterprise and enhance customer outcomes and experience. The author has dubbed in-house teams 'law's astronauts.' They operate within a corporate environment, are increasingly aligned with business purpose, goals, metrics, and customer-centricity, and are increasingly operating cross-functionally and proactively. In-house portfolios are expanding and more complex, even as their budgets and headcounts are shrinking. A response to this squeeze necessitates doing things differently and developing a growth mindset. Business has not directly shaped or managed this process, but it has created an environment where CLO's and GC's must do things differently. In-house teams have become (albeit to varying degrees) proactive, strategic, tech-enabled, data-backed, value-oriented, and results-driven. Most importantly, the in-house legal function is becoming integrated with the business and its customers. To effect this transformation has necessitated in-house teams to adapt to the speed, complexity, risk, uncertainty, and competing stakeholder expectations of business. That has, in turn, required a change in the in-house mindset, culture, and perception of legal's purpose and role in digital/AI-era business and society. In-house legal teams' alignment with corporate objectives and collaboration with various business units demonstrates that legal can operate in a corporate environment without ceding its professional independence. The expansion of the in-house team's enterprise role has been accompanied by a shift in market share allocation. In 2000, companies typically sourced 70-80% of legal work to law firms. Corporate teams now account for 54% of all legal spend. The remaining balance goes to law firms, ALSP's, consultancies, and an array of other niche providers. The gradual shift in market share is about to become sudden. AI will drive a spike through the law firm economic model, hollowing out the bottom and middle levels of its pyramid. This will be accompanied by a shift from output (value) as the billing basis, not input (hours). That will open the door to the integration of all legal product and services providers and end the economic, mindset, and cultural divide separating in-house teams and their supply chain. The stage has been set for a true structural paradigm change in legal delivery, one where provider sources are integrated across the supply chain. That is business-driven legal transformation. It does not spell the end of law firms, but it means that they will be very different than they are today. AI is the greatest-- but by no means the only—challenge facing the leadership of traditional law firms. Forrester, a market research group, projects that almost 80 percent of jobs in the legal sector will be significantly reshaped by AI technology. A 2023 Goldman Sachs report on the effects of AI on economic growth, indicates that 44 percent of legal tasks could be automated using AI tools. While the percentages relate to tasks, not jobs, mindset change will be required to adjust to ongoing upskilling as well as to new structures, models, workforces, and ways of delivering legal products and services. The challenge of transition is elevated because it is accompanied by increased workloads, headcount reduction, and elevated business and customer expectations. Firm leaders are also confronting other issues related to their legacy firm structure and model. A partial list includes: the generational divide separating older and younger partners, a dearth of AI-native talent, peripatetic partners, and brand differentiation (apart from a handful of elite firms) It's little wonder why firm leaders have agita. Last year's law firm profits may be up for many large corporate law firms, but so too is uncertainty about the sustainability of their economic model. Another indication of the model's fragility is white-hot PE interest in the long dormant legal industry (a positive and negative development for firms), What will the legal marketplace look like when AI becomes an integral component of strategic planning and delivery? Whether that will happen is no longer in question. When it does is anyone's guess (smart money is betting sooner than you think). One thing is clear: what has passed for 'legal transformation' to date will pale compared with what is about to unfold. Recommendations For Legal Mindset And Cultural Adaptation The following recommendations are a sampling, not an exhaustive list, of issues to be considered. While the focus is on the corporate segment of the legal market, the recommendations apply equally to the retail (people) part. The latter is grossly underserved and presents an enormous opportunity to 'do good and do well.' Conclusion Change no longer occurs over centuries, generations, or decades; it is constant. The time separating present from future has been compressed. That is creating new risks and greater uncertainty, as well as opportunities that precedent, best practices, and fixed mindsets alone can no longer address. Clayton Christensen, the father of disruptive innovation theory, captured the zeitgeist of 21st century business: 'Best practices are a great way to institutionalize what you know. But they're also a great way to institutionalize ignorance if you don't keep revisiting them.' The legal function must balance stare decisis with a growth mindset and culture in synch with digital/AI-era business and society. To do so requires that it reimagine itself and what it delivers—as business has--to meet the needs of end-users of its products and services. It must engage in the same reverse-engineering process that business has embarked on. These are blueprints the legal industry can borrow from and, as Christensen admonishes, 'keep revisiting them.' Curiosity, creativity, constant learning, thoughtful experimentation, foresight, agility, and an empathetic team orientation are key attributes of an AI-era legal function. They must be accompanied by a holistic focus on business, societal, and global developments, particularly macroeconomic, sociopolitical, and other forces that are reshaping life and business. A legal function with this mindset and culture will once again attract 'the best and the brightest' to it from multiple fields. It will reclaim its purpose, elevate its standing, and better serve business and society in real-time, AI-era world.
Business Insider
3 days ago
- Business Insider
I lost my internship after talking about pay. I flew to New York anyway and networked my way into a new role in 2 weeks.
This as-told-to essay is based on a conversation with Aaron Chen, a rising sophomore at UC Berkeley. This interview has been edited for length and clarity. Business Insider has verified Chen's employment history. The startup that pulled his offer did not respond to a request for comment. After a few calls with a crypto startup in New York, I was offered a summer internship over email in March. I signed the non-disclosure agreement with them. I was really happy as that was pretty late for recruitment, and I was stressed. Most upperclassmen got an offer in December. In June, I hopped on a call with the head of operations to talk about compensation. I might have asked a little too much, but I left room to negotiate. Product management internships typically range from $40 to $50 per hour in New York. Considering my combined skills in frontend engineering, UX/UI design, and motion graphics, along with my ability to support marketing, I proposed an hourly rate of $45. Five days before I was set to fly, they replied: "We do not have any budget for this internship, or any additional head count for that matter." I wrote in my email that I was open to discussing this, but they did not want to continue this conversation. I had already booked a flight to New York, paid for rent, and found a roommate to share it with. I was on a bus crossing the Bay Bridge when the email came in. I sent a goofy selfie to my sister saying, "Guess who's unemployed now?" But within minutes, reality hit me, and I started crying at the back of the bus. I called my parents, friends, and roommate. They were like, "Just go to New York and have fun." They insisted on supporting me in following through, and now I'm here. Straight off the plane and into networking I was on my own, and I searched for things to do in New York, specifically in tech. The first two weeks were pretty rough. I hopped around during New York Tech Week, which began the day I landed. I dropped off my bags and went straight from JFK Airport to IBM's office, running on zero sleep. Every day, I juggled different events, met different people, and networked, trying to get my foot in the door and establish myself in the city. I signed up for probably over 60 events in the span of a week. In the second week, I attended a crypto conference. I met a part-time blockchain builder and part-time professor from Stanford, who offered to circulate my résumé. By that time, I had already applied to around 50 companies and asked at least 20 people in my network to share my résumé and portfolio, hoping to find anyone who might be hiring — a long shot since it was already June. Thanks to the Stanford professor and folks in my blockchain club, I interviewed with six companies, and I really connected with a founder from Axal, an Andressen Horowitz-backed crypto startup. After our first interview, he messaged me at 3 a.m. on a Friday with the files for the take-home assignment. I was already awake, working, so I dove right in. Over the next two days, I pulled all-nighters designing, coding, and engineering the interface. At the final interview on Monday, I walked him through my design process, code, repository, and everything I built. He offered me the role on the spot. We went back and forth a bit on compensation, but things went smoothly. I got the official offer in my inbox, and this time, I signed it for real. I'm their fastest hire ever, from first contact to offer in just four days. It's been a chain of networking that put me in the position to even interview for the role. Everything happening literally within two weeks of me landing in New York with no job, no backup plan, still feels incredibly surreal to me. Summer motto: I have nothing else to lose It was really difficult to turn my mindset from being disappointed, anxious, and stressed to "I'll just take whatever life gives me." Accepting and embracing that reality has helped me so much because that allowed me to not withhold any of my energy or hold back when I go to networking events. I have nothing else to lose — that has been the motto of my summer. I am so happy I came to New York to meet the people I met and be part of the opportunities I've had. People who are older than me always tell me success comes in different ways, and I've always found it so corny. I truly believe that now.
Forbes
3 days ago
- Forbes
Stanford Analyzes Worker Preferences For AI
workers with AI getty Many of us have internalized this notion that we're soon going to be working side-by-side with robots, or at least AI agents and entities. So as humans, what do we want these digital colleagues of ours to do? How does delegation work? A Stanford study recently went into this where authors surveyed 15,000 workers in over 100 types of jobs, to see what they really thought about AI adoption. I thought this comment by one of the authors sums up the purpose of the report well: 'As AI systems become increasingly capable, decisions about how to deploy them in the workplace are often driven by what is technically feasible,' writes project leader Yijia Shao, a Ph.D. student in the Stanford computer science department, 'yet workers are the ones most affected by these changes and the ones the economy ultimately relies on.' In other words, it's the front-line workers who are going to be most affected by these changes, so we might as well hear what they have to say (in addition to doing all kinds of market research.) There's a reason why the suggestion box is a time-tested element of business intelligence. Technology has to be a good fit – it's not something you just implement carelessly, throwing darts at a wall, and then expecting all of the people involved to sign on and go along for the ride. Some Results In terms of actual study findings, the Stanford people found that a lot of it, as Billy Joel famously sung, comes down to trust: 45% of respondents had doubts about reliability, and a reported 23% were worried about job loss. As for the types of tasks that workers favored automating, the study provides a helpful visual that shows off various must-haves against certain danger zones of adoption. Specifically, Stanford researchers split this into a 'green light zone' and a 'red light zone', as well as a 'low priority zone', and an 'opportunities zone' featuring uses that workers might want, but that are not yet technically viable. Uses in the green light zone include scheduling tasks for tax preparers, quality control reporting, and the interpretation of engineering reports. Red light uses that workers are wary of include the preparation of meeting agendas for municipal clerks, as well as the task of contacting potential vendors in logistics analysis. There's also the task of researching hardware or software products, where surveyed computer network support specialists seem to prefer to do this type of work themselves. I thought it was funny that one item in the low priority zone was 'tracing lost, delayed or misdirected baggage,' a job typically done by ticket agents. It explains a lot for those legions of hapless travelers entering their faraway AirBnBs without so much as a toothbrush. As for opportunities, it seems that technical writers would like AI to arrange for distribution of material, computer scientists will largely sign off on technology working on operational budgets, and video game designers would like production schedules automated. Why Automate? I also came across a section of the study where researchers looked at reasons for automation desire on the part of survey respondents. It seems that over 2500 survey workers want to automate a task because it will free up time for other kinds of work. About 1500 cited 'repetitive or tedious' tasks that can be automated, and about the same number suggested that automating a particular task would improve the quality of work done. A lower number suggested automating stressful or mentally draining tasks, or those that are complicated or difficult. The study also broke down tasks and processes into three control areas, including 'AI agent drives task completion', 'human drives task completion' or 'equal partnership' (and two other gradations). You can see the entire thing here , or listen to one of my favorite podcasts on the subject here . One of the headline items is a prediction of diminishing needs for analysis or information processing skills. That connects with more of a focus on managerial, interpersonal or coordination job roles. However, how this will shake out is concerning to many workers, and I would suggest that 23% of respondents worrying about job displacement is a wildly low number. Almost anybody anywhere should be worried about job displacement. Regardless of what happens in the long term, many experts are predicting extremely high unemployment in the years to come, as we work out the kinks in the biggest technological transformation of our time. Anyway, this study brings a lot of useful information to the question – what do we want AI to do for us in enterprise?
