Consulting Psychology Journal

This study investigated how prior career experiences imprint on individuals’ behaviors, particularly in military contexts, shaping their transition into civilian life upon retirement. Resistance to change, one’s tendency to resist or avoid making changes, and personal sense of power, one’s perception of their ability to influence people and resources, often become by-products of military institutionalization, influencing military-to-civilian retirement transition and well-being. A moderated mediation model was proposed wherein personal sense of power would moderate the indirect relationship between resistance to change and well-being, mediated by transition difficulty. The sample was comprised of retired Indian Army personnel (N = 256). Confirmatory factor analysis validated the scales culturally, and Hayes’ PROCESS Macro was used to test moderated mediation. Findings reveal that resistance to change and transition difficulty negatively affect well-being. Moreover, transition difficulty partially mediates the relationship between resistance to change and well-being. Notably, personal sense of power moderates this mediation, acting as a buffer. The study underscores the significance of organization-relevant dispositional factors in comprehending the challenges of military retirement and their implications for overall well-being. The study provides recommendations for addressing dispositions such as resistance to change and personal sense of power through interventions like preretirement counseling, scenario-based exercises, growth mindset training, and confidence-building workshops to help veterans navigate transitions more effectively.

This article reports the results of, and discusses methods for, using a behavior-based 360-degree emotional intelligence (EI) assessment to help determine the readiness of frontline leaders to step up into more senior leadership positions. Participants (n = 485) were frontline school leaders in a public school system who were rated by 2,435 raters on a 360-degree leadership assessment measuring leadership performance proficiency, the Genos Social and Emotional Competency Survey, and two global items measuring leadership capability: specifically, a single item measuring how well the participants interacted with others at work and a single item measuring the participants’ overall job performance. The EI 360 was shown to account for an additional 17% of the variance in how well the participants interacted with others at work and an additional 8% of the variance in their overall job performance over the leadership performance proficiency. Participants (n = 70) deemed “not yet ready” for more senior leadership positions (based on low observer-rated EI scores) participated in a longitudinal EI development program. Their EI was then retested using the same raters 6 months or more later. Comparisons of their Time 1 and Time 2 EI 360 results show that the EI development program improved how well participants demonstrated their EI by on average 43 percentile points. Although further research is needed to substantiate the claim, we argued these results show that an EI assessment can contribute significantly to organizational decisions on leadership talent above and beyond the more traditional measures used in this context.

The theory of emotional intelligence (EI) grew out of research at the intersection of emotion and cognition and originally focused on individual ability and self-perception of ability. We argue that to fully understand how EI influences work-related outcomes in organizations, in addition to these individual variables, we need to examine how organizational factors create opportunities (or barriers) for the enactment of emotionally intelligent behavior (EIB). We discuss three groups of organizational factors: leader EIB, team EI climate (group behavioral norms), and organizational culture (values and practices). We present a model describing how these organizational factors moderate individual potential to shape EIB as a proximal outcome, which in turn predicts distal outcomes related to work well-being, interpersonal effectiveness, and performance. Directions for future research and practical applications for how organizational psychologists and consultants can boost both individual potential and organizational opportunities for EIB are discussed.

We examine evidence for the validity of different measures under the label emotional intelligence (EI). Some measures are valid for the assessment of EI and others are valid for the assessment of socioemotional attributes (SEA). The constructs of EI and SEA are defined and measures of each described, along with the mental response processes the measures elicit: test-takers’ abilities, self-estimated attributes, or observer reports. Both EI and SEA measures are valid but for distinctly different purposes, and the two classes of measures make different predictions. We add our voices to those who have advocated for dropping the EI label from SEA measures to more clearly draw the distinction between the two. Being clearer about constructs and measures will enhance consulting in the workplace and other applied settings.

Leadership versatility refers to the flexible, balanced, and situationally appropriate use of a broad range of opposing yet complementary leader behaviors. This article presents a definition and measure of versatility along with an explanation for its increasing importance in modern organizations and empirically examines two general propositions: first, that leader versatility can be quantified in terms of a hierarchical structure that distinguishes complementary behaviors in the interpersonal domain and in the organizational-task domain which, together, cohere in a higher order factor; second, that leader versatility predicts team performance and leader effectiveness with differential effects for versatility in the interpersonal and organizational-task domains. Analyses of ratings for 1,861 upper level managers and executives from dozens of American corporations representing several industries provided support for both the measurement of versatility and its relationship with team engagement, team productivity, and overall leader effectiveness. Implications are considered in terms of future research on versatility and recent, conceptually similar models of leadership for disruptive environments.

This article details the state of the art in measuring emotional intelligence (EI) in workplace settings, with a focus on the needs of practitioners who want to put scientific findings to use. It starts by defining EI as an umbrella construct that consists of a series of related yet distinct facets. Rather than focusing on theoretical models of EI, the article is organized around three measurement models—namely, self-report, ability testing, and observer report—and elaborates trade-offs based on each method’s strengths and weaknesses. Self-reported EI is highly correlated with personality traits such as agreeableness, and it is best conceptualized as confidence and motivation rather than intelligence. Self-reported EI is no more appropriate for hiring and promotion than are self-reported technical skills, but it can be valuable for developmental use, particularly when juxtaposed with other EI measures to highlight gaps in self-awareness that represent blind spots or hidden opportunities. Self-reports are also important for career counseling because self-perceptions and actual abilities can drive decision-making separately. Ability-tested EI shows greater validity for distinguishing EI from personality and other constructs, although ability reports can be more resource-intensive to administer and there are challenges in defining “right answers.” Finally, observer reports are valid and reflect people’s competencies in daily use more than their hypothetical best performance. The article emphasizes the importance of matching the method of measuring EI to the goal for doing so and suggests the value of all three types of measures in combination.

Team coaching is a relatively new and emerging field, with always evolving ideas around what it is and how it differs from team facilitation and development (Hackman & Wageman, 2005). Team-coaching programs are in many ways still in their infancy, with different curricula being developed across different institutions and training providers, however with an overall agreement that they need to differ from the training of individual coaches. After all, individual coaching is about individual learning and development and the psychology of the dyad, while team coaching is about team reflection, team development, and group dynamics, which can be very different from dynamics in a dyad. But what about the supervision of team coaches? What do current supervision models have to offer team coaches and their practice? Over the last 9 years, we have been experimenting, in the context of a team-coaching program, with a new group supervision method that specifically benefits team coaches and consultants who work regularly with intact teams. In this article, we want to initially share some thoughts on the role of the parallel process in supervision and how it has shaped our approach to team-coaching supervision. We will then describe our method, looking at the impact we have noticed and exploring the benefits and drawbacks of using it in an open or closed supervision group. Some reflections on the role of the supervisor will be offered, and we will conclude with some thoughts on the implications for supervision.

The purpose of the present study is to understand how South Asian American women bring their ethnic–racial identity (ERI) to work, in what ways do organizations currently acknowledge South Asian ERIs, and what can organizations do to better support South Asian American women’s ERI development. This study utilized qualitative research methods in the form of an open-ended survey to gather insights from South Asian American women. Thirty-eight women responded to the survey and shared experiences of their ERI at work. Results revealed that South Asian American women would like their organizations (i.e., workplaces) to acknowledge their ERI by being inclusive of cultural holidays and encouraging them to share their culture, which may be key factors of their retention. Leaders, consultants, executive coaches, and other organizational practitioners can utilize the findings to foster a more inclusive and diverse workplace that supports South Asian American women’s ERI development and career progression.

What’s It Mean? Implications for Consulting Psychology This special issue is important to consulting psychologists, executive coaches, human resources practitioners, leaders, boards, and others in varied professional spaces regardless of specialty. It serves as a reminder of two communities that are often invisible—frequently overlooked in the workplace generally, often excluded in DEI initiatives—with South Asians often not seen as Asian by Americans (Currier, 2024) and Arabs, because they were essentially erased, being forced to identify as White on the U.S. Census and other government forms until 2024 (Stepansky, 2024). This had implications in terms of their voice being lost. These two communities, despite their essential invisibility, are also simultaneously hypervisible due to bias and discrimination. We hope this issue will shed light on some of the experiences faced by people within these communities. Findings can be used by consultants and executive coaches and other professionals to more effectively work with clients from these communities and create more inclusive and equitable professional spaces for South Asians and Arabs. This is a call to not only support these two communities but a larger call to support all marginalized populations; otherwise, we ignore a huge swath of professionals, their needs, and their challenges to work at capacity due to bias and discrimination and we ignore their potential in professional spaces.

Arab/Middle Eastern North African (AMENA) women face mistreatment in professional spaces; however, research is limited. We argue that gender harassment exacerbates experiences of burnout in the workplace, negatively influencing job satisfaction. In addition, we argue that AMENA women’s experiences of gender harassment likely function as an additional job demand, heightening the influence of burnout on job satisfaction. Data were collected from 128 AMENA women on gender harassment, exhaustion, and satisfaction with pay, promotion, and supervision. Muslim AMENA women reported less supervisor satisfaction compared with Christian and nonreligious AMENA women. We also found that infantilization was the key type of gender harassment that predicted job satisfaction. Last, infantilization moderated the relationship between exhaustion and satisfaction with pay. When exhaustion was high, AMENA women experiencing high levels of infantilization were less satisfied with pay than AMENA women experiencing less infantilization. Both exhaustion and infantilization were directly related to less satisfaction with promotion and supervision for AMENA women. Implications are discussed for human resources professionals and consultants.

Information disseminated about particular groups feeds stereotypes and attitudes, which in turn feed prejudice and discrimination. There is a history of conflating Arabs and Muslims with terrorism, incited and perpetuated through media rhetoric, Hollywood, and political speeches, which has normalized racism and xenophobia against these groups. The impact of the media and the resulting sociopolitical environment toward Arabs and Muslims has culminated in discriminatory hiring practices, overrepresentation in unemployment, and perceptions of Arabs and Muslims as lacking warmth and work-related competencies and has had negative ramifications on the well-being and job satisfaction of Arabs and Muslims. According to the Equal Employment Opportunity Commission, the number of religion-based employment discrimination claims has dramatically increased across all states of employment over the past two decades. The Equal Employment Opportunity Commission also noted a rise in claims made by Arabs specifically and a 250% increase in claims for those perceived to be Muslim, Sikh, Arab, Middle Eastern, or South Asian. Systemic racism hurts everyone; human development and societal health are hampered by a lack of knowledge and exposure to marginalized groups. To enhance societal and organizational health, it is essential to create inclusive environments that directly name and challenge the stereotypes and barriers faced by Arabs and Muslims by facilitating generative interactions and enacting policies to counteract discriminatory hiring and promotion practices.

Building effective and inclusive workplaces in Canada requires addressing the intersectionality of identity in the workplace, including consideration toward how racism impacts experiences in that context. This article examines how racism, especially toward Arabs and South Asians, influences their experiences in the workplace and the ways the workplaces can strive to be more inclusive. The study utilized a qualitative framework to conduct semistructured interviews and a survey. Groups approached included South Asians, Arabs, and others, as we wanted to understand how others perceive South Asians and Arabs in the workplace and can support inclusion. Data analysis entailed a thematic analysis that incorporated a literature review to develop a theoretical framework around three central themes: intersectionality, othering, and internalized racism. These themes were further refined as participants described additional understudied aspects of identity that influence workplace experience: status in Canada, parenthood, cultural background, and language. Experiences of othering, both internalized and external, were also identified as contributing toward a welcoming versus unwelcoming workplace. The findings indicate that there is ongoing racism, discrimination, and marginalization at Canadian workplaces toward people identifying as South Asian and Arab but also broadly toward people who identify as Black, Indigenous, and people of color, compounded for those who are women or parents or both. However, the findings also contribute valuable insights into ways to intentionally create workplaces for people to express and share their identities and be supported in addressing the challenges these identities create.

This article addresses the artificial intelligence (AI) legal risks encountered by consulting psychologists and managers leading organizations in the United States pertaining to intellectual property and confidentiality. The article first provides an overview of the relevant legal principles of patent, copyright, trademark, trade secret, and confidential information. The article then discusses three significant risks: the risk that AI use will result in the infringement of third-party intellectual property, the risk that an organization or individual will be unable to protect ownership rights in an invention or work developed using AI, and the risk that the use of AI will result in the loss of confidential information or trade secrets or both. Finally, the article discusses specific guidance to consultants and managers on steps they can take to manage the legal risks.

The present article identifies four types of data that can be analyzed using artificial intelligence- (AI-) powered hiring tools assessments in various stages of the selection process: (a) data from traditional psychometric instruments, (b) data from AI-based assessment tools, (c) data from the “digital footprint” of given individuals, and (d) direct and indirect observations. In all methods, AI makes predictions and supports hiring/promotion decisions using historic data (“training data”). Understanding both the nature of these data and the underlying functionality of the AI is crucial when it comes to evaluating ethical and legal issues that might arise when employing AI in assessments, such as discrimination and inequities. Questions addressed here include the following: (1) Does a bias already exist in the data on which the AI system has been trained? (2) Does the algorithm have parameters based on psychological theories and evidence? (3) Does the AI system allow the “black box” to be opened? The article also notes that AI-driven assessments have the potential to deliver more precise evaluations of individuals. Additionally, because these assessments rely on a wealth of data and on numerous interactions drawn from real-life circumstances, they can address typical rather than merely maximal behavior, with the typical case capable of being measured via psychometric tests. The article furthermore discusses a number of ethical issues that arise in personnel selection using AI.

Artificial intelligence (AI) is rapidly infusing organizations and consulting practice but ethical guidance specific to AI lags. This article identifies ethical duties and responsibilities of consulting and industrial–organizational psychologists, AI content developers, and managers when working with AI. The article contextualizes contemporary AI (broadly defined) and AI ethics in their long history, but it notes that the complexity of ethical and legal issues associated with AI have greatly accelerated. The article demonstrates that although there is little in the current ethics codes of psychologists specifically addressing AI, the existing ethical standards clearly are applicable. Other codes of ethics are also considered in the article, demonstrating that the same ethical constructs (in this case, beneficence/nonmaleficence; competence; confidentiality; informed consent; data ownership, usage, and retention; and scientific basis of products and processes) are relevant to other professions working with AI. Emerging AI laws in the United States and the European Union are briefly discussed. Ethical roles for consulting and industrial–organizational psychologists at the individual, group, and organizational levels are identified and a case provided. Some ways that psychologists can maintain their ethical requirements when working with others (e.g., managers and product developers) are also discussed.

Artificial intelligence (AI) has the potential to impact organizational performance in ways unimagined even a few years ago. Although AI is not new, its rapid advancement has heightened the awareness of its strategic business value concurrent with the ethical implications and potential for harm that AI systems present. The article argues that businesses face ethical dilemmas in parallel with pressure to adopt AI as a business opportunity. It discusses AI’s growing impact on business model innovation, organizational strategy, and operational effectiveness in light of the need for ethical AI systems and practices. Calls for AI governance solutions are mounting and, within organizations, will involve structural, process, and policy considerations likely with ethics as central. These elements are discussed as specialized management practice components unique to AI. Several governance structures and organizational design considerations are discussed as means to enable disciplined, ethical, and responsible AI use. The article concludes with three recommendations for AI deployment that balance ethical considerations with financial profit motives and suggest that the two are not mutually exclusive.

Along with providing extraordinary benefits, artificial intelligence (AI) poses risks of harm to people. This article focuses on two ethical concerns with AI that are of particular concern to consulting and industrial–organizational psychologists: harm to people’s well-being and harm to interpersonal relationships. AI has the ability to affect people’s perceptions and experiences when they interact with each other in AI-mediated communication by rewriting and autocorrecting people’s writing, changing physical appearances, and redirecting people’s attention to information or ideas that could marginalize or create bias against people. AI is also able to influence people’s ways of thinking and feeling in human–AI interaction. It can cause them to react more positively or negatively to information and to anthropomorphize AI using different types of imagery and language patterns. When AI is used in automated performance-management platforms, it can direct employees to work harder and longer than they want to and cause harm through stress and burnout. Many codes of ethics require consultants and professionals to take reasonable steps to avoid harming the clients and people with whom they work and to minimize harm where it is foreseeable and unavoidable. This article identifies how these AI capabilities may cause harm to individual, interpersonal, and group well-being even when the same AI may also provide positive contributions. It provides guidance for consulting and industrial–organizational psychologists to research, create, and deploy AI in healthy ways and mitigate harm to employees.

Although still in its infancy, the proliferation of artificial intelligence (AI) in personnel selection has sparked concerns regarding potential implications for bias, fairness, discrimination, and unethical decision-making. This article delves into the complex issue of AI-based personnel selection as it pertains to the preceding concerns, exploring key definitions, bias-assessment methodologies, legal frameworks, professional and government considerations, and ethical dilemmas unique to AI-based selection. The critical role of consulting and industrial–organizational psychologists in ensuring fairness, validity, and nondiscrimination in the selection process is emphasized. The need for transparency, informed consent, and a holistic consideration of diversity/validity in the design of AI-based selection systems is explored. The role of an applied independent auditor, impartial and objective, is discussed in the context of maintaining ethical standards and mitigating conflicts of interest in auditing AI-driven selection processes. Ultimately, this article underscores the multifaceted nature of managing AI-based selection, calling for interdisciplinary collaboration, ethical prudence, and ongoing scrutiny to ensure the responsible use of AI-based methodologies in personnel selection.

The purpose of this contribution was the translation of recent research evidence regarding factors contributing to effectiveness in the helping professions in general, and in coaching outcome studies in particular, to the practice of workplace and executive coaching. It is shown that rigorous statistical results from effectiveness studies can be translated to benefit training, coach development, and supervision of coaches and help professional coaches to bring out and hone competencies and skills that are demonstrably informed by the evidence base in coaching. For this purpose, the main outcome studies and meta-analyses in the helping professions are first summarized in general terms, including the evidence for general effectiveness, the evidence for the importance of common factors in producing that effectiveness, and some clear indications that factors stemming from technique and approach do not reach statistical significance, that is, that all professional approaches work. Moreover, we review good indications in outcome research for the differential use of particular approaches for dedicated purposes, as well as some evidence for a demonstrable added value of the participation of the coachee in the choice and application of interventions. Plausible conclusions are drawn from these findings, such as the importance for coaches to be aware of (a) their own preferences within models and approaches, (b) strengthening of common factors in their own effectiveness, and (c) allowing the coaching contract to determine the nature of the interventions offered. A new model of coaching contracts is offered, based on the presenting anxieties of the coachee.

The present study examined four elements of the working relationship between professional (executive) coaches and clients that might predict the extent to which clients make progress toward their goals (as judged independently by clients and coaches): (a) coach supportiveness, (b) the extent to which coaches challenged clients to think or behave differently, (c) client engagement, and (d) the extent to which the coach helped clients envision and articulate their core values and ideal self (aspirational clarity). Unique among studies on the predictors of coaching effectiveness, this study also examined whether “actionable planning” (clients’ subjective sense of the extent to which they cocreated effective, concrete action plans with their coaches) could help explain the associations between these four factors and goal progress. Results showed that when progress was rated by clients, all four factors were related to goal progress, but only three exhibited unique predictive value when examined simultaneously. Actionable planning partially mediated these associations. However, when goal progress was rated by coaches, only client engagement levels and aspirational clarity uniquely predicted goal progress, and actionable planning was not a significant mediator of either variable.

Despite advances with high-potential talent identification, there is a lack of empirical evidence and agreement for how potential should be measured and utilized. Global measures of potential focus on employee advancement to higher organizational job levels. However, these models lack the specificity and foresight to identify lateral moves that may benefit both the employee and the organization. This study was specifically designed to develop and evaluate a behavioral framework aimed at more effectively determining employee suitability for specific and targeted roles. Additionally, it provides a methodology that can be adapted for similar applications in various other organizations. Findings demonstrate support for building a high-potential model that integrates multiple, theoretical constructs and using behavioral ratings to help predict employee readiness for future growth opportunities.

A wide range of instruments is employed within the talent selection pipeline, and, with the progressive evolution of artificial intelligence (AI), the development of AI solutions has made inroads into certain areas of staff selection, notably the processes of reviewing applicant resumes and conducting asynchronous video interviews. However, the use of AI models with machine learning to interpret text-based assessment center (AC) simulation responses has remained largely unexplored. The main aim of this study was to assess the convergent and criterion validity of an AI model. A secondary objective of the study was to see if the AI algorithm utilized more scale points in rating written simulation responses compared to human assessors’, whose scores typically suffer from range restriction. AI was used to analyze the text-based AC simulation outputs of 15,000 leaders, comprising 33 million words, and 38 competencies were discovered. The AI model was then used to score the simulation results of three separate samples of leaders to assess its convergent and criterion validity. The results showed convergent validities ranging from 0.63 to 0.73 and criterion validities ranging from 0.51 to 0.54. In terms of range utilization, the standard deviation indicated that the AI model utilized a wider range of scores than human assessors did. Empirical results presented in this study across three samples suggest that AI algorithms can score written text in a similar way as human raters. Second, the AI algorithms are better at utilizing the full range of scores available. The AI model seems to be on par with the human rater, with accuracy and recall metrics at 0.91, indicating the possibility of augmenting or replacing the human assessor.

In leadership development, 360 assessments are multirater instruments in which leaders rate themselves on leadership competencies and are assessed by several raters (e.g., peers, direct reports, bosses). Such assessment methods afford valuable opportunities for both leaders and practitioners alike; however, they also present thorny challenges, including those related to scoring. We propose a Latent Approximation Method (LAM) for scoring 360s that is based on recent modeling advances for multirater data and provide a preliminary empirical evaluation of that method. To an international sample of nearly 17,000 leaders and nearly 150,000 raters, we applied LAM scoring to a 360 measure of several leadership competencies. We examined associations among LAM scores, explored associations between LAM scores and standard averaged scores, and evaluated the incremental predictive utility that LAM scores bring (beyond standard scores) to the prediction of criterion variables. Replicating across subsamples, results revealed considerable overlap between LAM scores and standard scores. Moreover, LAM scores provided significant but small incremental predictive power over Standard Averaging Method scores. These results indicate limited value of LAM scoring for practitioners, and we discuss the implications of these findings for both research and applications using 360 assessments.

The CliftonStrengths Assessment (CSA), published and sold by the Gallup Organization, is a personality assessment designed to identify areas of an individual’s inherent talents from 34 strength themes. The CSA has grown in popularity and is used across a variety of contexts. Within institutions of higher education, the CSA has been implemented in first-year seminar courses, subject-specific courses, advising, athletics, student leadership roles, team building, and leadership roles in higher education administration. The present article evaluates the psychometric properties, methodology, and potential outcomes of implementing the CSA within higher education. The authors conclude that the current available evidence for implementing the CSA within higher education is insufficient, and additional research on the CSA could be illuminating and welcomed. The authors also provide recommendations for those working in and consulting to institutions of higher education who seek to implement positive-psychology frameworks to benefit university students and communities. In selecting programs and implementing interventions, individuals and institutions should carefully consider: (a) the available empirical, peer-reviewed support for a program and intervention and (b) the match between the supported uses of a program with their population and goals.

The presence of artificial intelligence (AI) and machine learning in consulting psychology is accelerating. Although consulting psychologists are beginning to understand that AI’s disruptive potential is significant, many still have a limited knowledge of its concepts, uses, and challenges. However, practitioners will increasingly encounter AI in many domains where they work and possibly compete with it. We present an overview of AI technology and discuss its growing use in the practice domains of consulting psychology. The fundamental elements of the so-called AI “black box” are discussed, including the basics of how AI algorithms are designed to function and learn. Given this understanding, we next discuss how AI is emerging as a technology impacting organizations, teams, and individuals specific to applications relevant to consulting practice. Within this context, we consider the roles that consulting psychologists can play in helping organizations implement effective, responsible, and ethical AI. The article concludes with a discussion of suggestions for AI’s responsible and ethical use in consulting psychology.