• 43 percent of audience respondents said new leadership practices emphasizing empathy will be the biggest game changer in balancing operational precision and empathy in the future.
• Part of creating a psychologically safe workplace is dependent on having empathetic leaders
• Good communication on the part of leadership topped a number of polls. Transparent communication from leadership was the top priority for fostering a human-centric environment.
• Nearly 40 percent of respondents said clear communication on how their contributions make an impact was the most effective way to engage employees in continuous improvement strategies.
• Change fatigue is real, and leaders have no choice but to recognize this challenge. They should listen to people’s concerns, validate their feelings and show some level of sensitivity before executing a change strategy.
• 35 percent of respondents said performance metrics and monitoring were the best approach. Another 32 percent said feedback and improvement loops should be the priority.
• People are not limited to employees. Ultimately, any process that a business is improving is meant to eventually make the customer experience better. Indeed, experts stress the importance of always keeping customers in mind.
• “When you have a customer pain point, it’s a lot easier to get buy-in for OPEX because it’s coming from your paying customers.”
• “When we look at our processes, how do we infuse intelligent automation, remove friction, ensure quality and really unlock value for our customers?”
• All people – employees and customers – want to know what’s in it for them whenever they face these major changes. Leaders can help people stay motivated. Creating Centers of Excellence (CoEs), which are focused on improving processes, is one way to empower people. 
• One way to keep people at the center of a business is to make them part of the solutions to your problems from the very beginning. This is more important in the age of AI and other advanced technologies. 
• “People are still a very important part of the process,”
• Some on PEX Network have suggested that leaders should manage AI technologies as though they are employees who are working alongside the humans.
• If leaders are committed to keeping humans in the loop even as they automate more processes, then they must help them overcome fears of potential job loss. 
• Automation and AI are there to enable employees to do more meaningful tasks.”

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• Level 1: Make existing work easier. (Same job, better tools.)

   

  This is where we click on the Microsoft Copilot or Zoom or Teams and the system analyzes a meeting, summarizes emails, or writes a document with our help. We do our jobs the same way we did before, but we now have a “super-productivity” tool to make it easier. These “add-on” use cases are emerging everywhere, and they already feel like a commodity.

• Level 2: Major steps eliminated, but the job is the same. (Same job, tools eliminate work.)

   

  At level 2 we automated a lot. Software engineers now use copilots to develop 70% of their code, so they’re spending more time testing and prompting the AI. Their individual coding skills may atrophy, but they can now work on more architectural issues.

   

  The “job” of software engineer may still be the same, but the output is far greater. So we’re making the same pay, doing the same work, but using highly automated tools.

• Level 3: Re-engineered work, partnered with agents. (New job, redesigned process, agents automate work.)

   

  At level 3 we go further: we re-engineer the process and the work. Imagine how McDonald’s replaced its counter workers with a kiosk, eliminating the “may I take you order please?” role.

   

  This took some major design effort but resulted in a whole new set of roles, workflow, and management structure in the restaurants. The “cost per burger” went down, and the customer experience is almost as good (not quite).

• Level 4: Autonomous intelligent agents, people training and managing the AI. (New job, redesigned process, people “manage” the agents.)

   

  At level 4 we go even further. Imagine an AI recruiter (Paradox does this) that could email a hiring manager and his team, gain feedback and requirements on a job and role, consolidate input, and create a total description. This Agent could then review this job against the company culture and pay policies, compare the job against similar jobs in the external market, and tweak the level, job title, and description to be competitive. And then it could start sourcing, and give the hiring manager and human recruiter a set of candidates ranked by various criteria.
• Our thesis is that AI is not a “job-replacement” technology, it’s a “SuperWorker empowerment” technology. In other words, most of these scenarios result in higher value jobs, higher pay, and value creation (not cost reduction) in the busines

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• Our recent discussions with tech leaders across industries suggest that four emerging shifts are on the horizon as a result of gen AI, each with implications for how tech leaders will run their organizations. These include new patterns of work, architectural foundations, and organizational and cost structures that change both how teams interact with AI and the role gen AI agents play.¹
• Factory pattern. In this model, leaders deploy autonomous gen AI–enabled agents that can collaborate and navigate the work end to end. This approach is best for predictable, routine processes within enterprise technology, such as log monitoring, regulatory technology updates, or legacy code migration.⁵Aamer Baig, Sven Blumberg, Arun Gundurao, and Basel Kayyali, “Breaking technical debt’s vicious cycle to modernize your business,” McKinsey, April 25, 2023. We’ve seen some promising early results from such an approach, with organizations modernizing code in nearly half the time by orchestrating gen AI agents to handle rote coding activities.⁶
• One of the challenges leaders may face is effectively blending these approaches to create a fluid, synchronized workflow as tasks move from human to AI and back to human. To support this work, tech leaders should consider developing a framework and governance and risk management strategy that guides their efforts.
• . For AI-led tasks, “factory” supervisors will be needed who can oversee and implement audit mechanisms, validate AI output samples, identify and correct any AI agent deviations from the intended behavior, and ensure the necessary governance and explainability are in place to maintain a high level of accuracy and trust
• First, the scale of innovation is expected to increase as IT directs more resources to strategic problem solving, closing out the backlog of business requests, and taking on new requests from the business.
• Second, as staff productivity increases, the speed at which IT can conceive, build, and launch capabilities is also expected to increase,⁹“Gen AI and beyond: Where else to focus now,” McKinsey, July 12, 2024. while the cost of that work will likely decrease.
• Super platforms. Super platforms represent the next generation of third-party business applications—such as collaboration tools, customer relationship management (CRM), or enterprise resource planning (ERP) solutions—with built-in gen AI agents. These agents are essentially commodities that can be rapidly put into service. A CRM super platform, for instance, could enable a user to not only run a sales report but automatically communicate with the company’s analytics tools without doing any programming.
• AI wrappers. These are essentially intermediary platforms that enable enterprise services to communicate and collaborate with third-party services via APIs without exposing their proprietary data. A bank, for example, may build a gen AI–enabled wrapper around an internally developed AI-driven credit risk model. The AI wrapper can then initiate any queries—for example, leveraging a vendor’s LLM to generate risk factors based on the bank’s customer data and credit scores. Once built, AI wrappers can easily interact with any third-party service, enabling IT to easily switch vendors when needed.

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• Idée reçue n°1 : « Le télétravail rend les employés moins productifs »
• Ce qu’en dit (vraiment) la science : à l’inverse, une étude de la Banque de France de 2021 a observé une hausse de productivité de 20 % chez les télétravailleurs. Plus concentrés, moins interrompus par les discussions autour de la machine à café, ils abattent plus de travail en moins de temps. Même son de cloche d’après une étude de l’INSEE de 2023, selon laquelle le télétravail à long terme pourrait améliorer la productivité de 10 %. En 2024, le Fonds Monétaire International enfonce le clou également en précisant que le télétravail réduit le temps de trajet, offrant aux salariés plus de flexibilité pour se consacrer à leurs missions. Résultat : un meilleur équilibre et des performances accrues.
• Idée reçue n°2 : « Les managers ne peuvent pas gérer à distance »
• Ce qu’en dit (vraiment) la science : pas d’inquiétude, la gestion à distance marche, et même plutôt bien avec les bons ajustements. Selon l’ANACT, les managers peuvent rester efficaces en développant de nouvelles compétences, comme l’écoute active ou la communication à distance. Résultat ? Une supervision adaptée et des équipes qui fonctionnent. La chercheuse Clara Laborie a démontré que le management à distance peut même améliorer les performances individuelles et collectives, à condition d’instaurer un climat de confiance et de bien-être. Une analyse menée par Michael Page met également l’accent sur l’importance d’une communication transparente et claire, couplée à des règles de fonctionnement spécifiques. En favorisant l’autonomie des collaborateurs, on renforce leur engagement, même à distance.
• Idée reçue n°3 : « Le télétravail détruit la culture d’entreprise »
• Ce qu’en dit (vraiment) la science : une étude menée par Klaxoon en 2023 explique que la culture d’entreprise peut non seulement survivre, mais aussi s’épanouir à distance, à condition de miser sur des outils collaboratifs efficaces. L’intégration et la valorisation des employés à distance renforcent leur engagement. Selon une analyse de Psico Smart de la même année, le télétravail peut même être une opportunité d’évolution. 82 % des dirigeants interrogés envisagent de maintenir des formes de télétravail, y voyant un atout pour réinventer les relations professionnelles. Enfin, une étude menée par Cisco en 2022 montre que le télétravail, bien accompagné, peut avoir des effets positifs sur la productivité et le bien-être. Deux piliers essentiels d’une culture d’entreprise saine.
• Idée reçue n°4 : « Le télétravail isole socialement et provoque des troubles psychologiques »
• Ce qu’en dit (vraiment) la science : les études nous montrent une réalité bien plus nuancée. Selon l’INSEE (2019), les télétravailleurs intensifs n’ont pas un état de santé mentale différent de celui des autres salariés, et leurs relations conviviales avec les collègues restent intactes. La distance physique ne signifie pas nécessairement une perte de lien social. Une recherche de l’Anses de 2023 souligne que l’impact du télétravail sur la santé mentale dépend des conditions dans lesquelles il est mis en place. Ce n’est donc pas le télétravail en lui-même qui pose problème, mais parfois son organisation. En 2023, Santé publique France va plus loin en expliquant que des éléments tels que l’aménagement de l’espace de travail et le soutien social permettent de prévenir les troubles psychologiques liés au télétravail.
• Ce qu’en dit (vraiment) la science : les données montrent que le télétravail n’est pas un frein à la progression de carrière, à condition que l’organisation s’adapte. Une étude de l’Université de Stanford de 2015 a révélé que les employés en télétravail augmentent leur performance de 13 %, et que leur taux de promotion est similaire à celui des employés en présentiel. La qualité du travail prime donc sur la présence physique. Un rapport de l’OIT de 2020 met aussi en lumière que le télétravail peut offrir des opportunités équivalentes, à condition que les entreprises adoptent des politiques inclusives et des outils de communication adaptés. Enfin, une enquête menée par Buffer en 2021 révèle que 45 % des télétravailleurs estiment que cela n’affecte pas leurs opportunités de carrière, et 23 % pensent même que cela les améliore, grâce à une meilleure visibilité de leurs résultats.
• Idée reçue n°6 : « Le télétravail coûte plus cher à l’entreprise »
• Ce qu’en dit (vraiment) la science : le télétravail est loin d’être une charge insurmontable pour les entreprises. Au contraire, il peut même leur faire économiser de l’argent. Une étude de Global Workplace Analytics de 2020 estime qu’une entreprise moyenne peut économiser jusqu’à 11 000 dollars par an par employé à distance à mi-temps. Ces gains proviennent de la réduction des coûts immobiliers, des dépenses en électricité ou chauffage, et des frais liés aux absences. Un rapport de la Banque de France de 2021 met également en avant que le télétravail favorise l’adoption de technologies innovantes, augmentant ainsi la productivité globale, ce qui compense largement les investissements initiaux. Une analyse de l’INSEE de 2023 montre, quant à elle, que le télétravail peut améliorer la productivité de 10 % à long terme, avec des gains financiers directs pour les entreprises.

• Idée reçue n°7 : « Le télétravail ne fait pas “pro” devant les clients »
• Ce qu’en dit (vraiment) la science : les études prouvent que le télétravail, loin d’entamer le professionnalisme perçu, peut même renforcer la satisfaction client. Selon une étude d’Eloquant de 2021, les consommateurs apprécient la flexibilité et la réactivité offertes par le télétravail, notamment dans les services clients. Ils ne le voient pas comme un frein, mais comme une adaptation à leurs attentes. Une analyse de TalenCo de 2022 souligne notamment que le télétravail améliore souvent l’efficacité des collaborateurs, ce qui se traduit par une meilleure qualité de service. La généralisation des outils de visioconférence renforce également la collaboration, et donc la satisfaction client. Le rapport de l’IFOP de 2021 précise que l’évaluation du télétravail par les clients est largement positive, l’efficacité des services prenant le pas sur d’éventuels biais liés à la distance.

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• 2x

  more likely to realize value from GenAI than other companies — top-performing companies highlight the benefits of making AI intrinsic to your business.
• An effective AI strategy, designed to deliver value at scale this year, takes a portfolio approach.
• “AI adoption is progressing at a rapid clip, across PwC and in clients in every sector. 2025 will bring significant advancements in quality, accuracy, capability and automation that will continue to compound on each other, accelerating toward a period of exponential grow
• The growing gap between AI leaders and laggards will extend to economies too. Businesses in the US, with its relatively flexible regulatory environment, may outperform those in the EU and China, which have more rigid regulations.
• Your workforce could double — thanks to AI agents
• If you think AI will shrink your workforce, think again. You’re going to welcome a host of new members to the team this year: digital workers known as AI agents.
• 41%

  of executives say that workforce issues, such as training, culture, or change in work are among the top-five challenges their organizations face in using GenAI.
• Thinking about agentic workflow as a fundamental part of your workforce strategy may be a big leap for many companies.
• “AI agents are set to revolutionize the workforce, blending human creativity with machine efficiency to unlock unprecedented levels of productivity and innovation.”
• ROI for AI depends on Responsible AI
• Risk management and Responsible AI practices have been top of mind for executives, as we predicted last year when we said 2024 would be a moment of truth for trust in AI. Yet there has been limited meaningful action. That will change. In 2025, company leaders will no longer have the luxury of addressing AI governance inconsistently or in pockets of the business.
• 46%

  of executives say that differentiating their organization, their products and their services is one of their top-three objectives for investing in Responsible AI practices.
• Business leaders, especially those driving AI transformations, will begin to champion this necessary oversight. They won’t wait for regulatory clarity. AI is moving too quickly and is too business-critical for that.
• To implement AI oversight that unlocks value, you’ll need a second set of eyes. This could come from appropriately upskilled internal audit teams or a third-party specialist conducting an assessment based on leading industry practices and standards.
• “Successful AI governance will increasingly be defined not just by risk mitigation but by achievement of strategic objectives and strong ROI.”
• AI will be a value play — and a boon for sustainability
• AI will accelerate the energy transition. It will also help companies meet their sustainability goals – especially those in emissions-intensive sectors like manufacturing, construction and transportation – if they take the right approach. AI requires so much energy that there’s not enough electricity (or computational power) for every company to deploy AI at scale.
• 63%

  of top-performing companies are increasing cloud budgets in order to leverage GenAI, while 34% say sustainability considerations are driving expected budget increases.
• But these near-term challenges shouldn’t overshadow the big picture. AI will be a driver for sustainability. Globally, it will likely speed up the shift to renewables.
• AI can potentially simplify compliance with a new wave of sustainability disclosure regulations in the United States, the European Union and elsewhere. The November election means the SEC’s climate-related disclosure rules will likely remain on hold, which may create a void that is filled by states following California’s lead and developing their own rules and requirements.
• “It’s just not true that AI is anti-sustainability. If you use it right, AI makes not just carbon targets, but every sustainability goal more accessible.”
• AI will cut product development lifecycles in half
• we’re confident that adopting AI in R&D can reduce time-to-market 50% and lower costs 30% in industries like automotive and aerospace. In many pharmaceutical companies, AI has already helped reduce drug discovery timelines by over 50%.
• 67%

  of top-performing companies are already realizing value in using GenAI for products and services innovation.

• “We’re just starting to feel the impact of how the multimodal vision and generation capabilities of AI will change product design and more.”

   
• AI will transform industry-level competitive landscapes
• 73%

  of executives say they’ll use GenAI to make changes to their company’s business model.

• Consumer markets

   

  Consumer-facing companies will deploy AI across their operations and business. AI will enhance marketing, supply chain management, financial operations and customer service. Many will revamp customer services with a mix of more engaging chatbots and AI agents that provide human staff with the exact information they need to assist customers

• Financial services

   

  The impact of AI is broad, but we’ve seen measurable impact concentrated with AI native startups and large financial institutions. There’s been a resurgence in the fintech space with AI native businesses focused on solving old problems with new platforms and business models. Similarly, we’ve seen many of the largest financial institutions experimenting with several common use cases.

• Health industries

   

  The use of AI in 2025 should be accelerated by a more flexible regulatory environment. The new administration is likely to shift oversight in this sector toward self-governance, creating more space for innovation. Pharmaceutical and medtech companies will be in the forefront of using AI to revolutionize their value chains, especially for drug and product development.

• Industrial products

   

  In 2025, a smaller group of industry leaders will begin to pull ahead of their peers. Those industrial products companies with higher quality data and more standard processes will use AI to improve efficiency and insights, accelerate R&D and slash go-to-market time.

• Technology, media, telecommunications

   

  In 2025, AI agents will start to reshape demand for software platforms, as companies use them to fill the gaps of existing systems, such as ERPs. With AI agents customizing and extending the life of software platforms, some companies may choose to invest less in premium upgrades.

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• Premier constat : le volume réel des émissions de gaz à effet de serre de cette filière représenterait plus du double du volume estimé dans les études précédentes.
• Le secteur de l’IA est très énergivore : chaque requête auprès d’un modèle d’IA serait 6 à 10 fois plus gourmande en électricité qu’une requête auprès d'un moteur de recherche comme Google.
• Aux Etats-Unis, les centres qui hébergent ces données consomment déjà 2 à 3 % de l’ensemble de l’électricité du pays, et cette consommation devrait tripler dans les 5 prochaines années.
• 40 à 50 % de l’énergie consommée servent à produire des données, 30 à 40 % sont consacrés au refroidissement de ces centres.
• Quant aux GAFAM, leur consommation cumulée d’énergie a plus que doublé au cours de ces 5 dernières années, au point de les faire renoncer aux objectifs Net Zéro Carbone qu’ils avaient annoncés
• d’électricité, ce qui les obligerait à restreindre leur consommation d’énergie dès 2027 et donc de ne pouvoir répondre à une demande dont la croissance est estimée à 160 % pour les deux prochaines années.
• En moyenne, les centres utilisés pour les modèles d’IA consommeraient 2,1 millions de litres d’eau… chaque jour, et un modèle comme ChatGPT, un demi-litre d’eau pour répondre à 10 à 50 requêtes.
• Le taïwanais TSMC, leader mondial de la fabrication des puces électroniques, utiliserait environ 157 000 tonnes d’eau par jour

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• Objectives are a specific result you’re trying to achieve within a time frame and with available resources. Think of them as the steps you will take to achieve the goal. An example of an organization’s objective might be to “Call all existing customers in Q3 with a special promotion to increase sales.”. For an individual, an objective might be to “Research all relevant HR certifications and register to earn one before the end of the year.”
• Goals are an observable and measurable end result having one or more objectives to be achieved. Goals are typically broad in scope versus an objective which is very specific. For example, a goal might be for an organization to “increase profits”. Or an individual might have a goal to “become certified”. 
• Outcomes are the measurement and evaluation of an activity’s results against their intended or projected results. Outcomes are what you hope to achieve when you accomplish the goal. Using the above examples, the organization’s outcome might be to “increase profit by 50% over last quarter”. That’s what the organization is trying to do. For an individual, the outcome could be “get a new job” or “get a pay increase” as a result of earning a certification. 
• A key principle of employee engagement is that employees need to see how their work has value.

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• Individual Improvements

   

  Research has shown that individuals can increase their capabilities in a relatively short period of time.
• The degree of improvement can vary widely according to skill level, experience, and profession
• Many organizations are at this stage. It requires little more than making gen AI technology and guidance available to employees.

• Collective Intelligence

   

  The effectiveness of a team depends on building and evolving a shared understanding of the work to be done together. Organizations that leverage gen AI to close gaps in understanding between people will gain significant competitive advantage over those that do not.
• Groups can use gen AI to identify and remove barriers to human-human collaboration, discover shared mental models of their work, reduce bias in decision making, and resolve conflicts more quickly.
• The key isn’t just teaching people to use AI; it’s creating a common language around what is possible. Teams we work with are discovering that they can work with gen AI almost as if it were another colleague.

• Transformation & Growth

   

  While improving productivity is valuable, gen AI’s real power is in reimagining how work is done altogether. Organizations that move beyond individual productivity improvements and collective intelligence can create entirely new sources of value.

• Visionary Innovation

   

  Once you build the habits and practices to reimagine internal processes, you can begin to transform how you engage with your customers, suppliers, and other stakeholders to create innovative new products and services. Here is where AI can be truly revolutionary and change the game entirely.

• Start with discovery (60 minutes)

   

  Cross-functional teams of four to six people inventory current gen AI usage and identify opportunities at each pyramid level.

• Prioritize use cases (30 minutes)

   

  Teams evaluate opportunities based on potential value creation and implementation feasibility. The focus isn’t on speed, but on quality improvements that matter to stakeholders

• Build to learn (90 minutes)

   

  Selected high-priority opportunities move straight to prototype development.

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