pwc, one of the world's four largest accounting firms (PricewaterhouseCoopers) released a report on the top 6 predictions in AI for 2025.
PricewaterhouseCoopers said.Generative AIThe advent of AI has made it easier to develop AI applications. A generalized large model requires only a small amount of customization to build products for different domains such as finance, finance, development, customer service, and so on.
Among other things, PwC specifically mentioned AI AgentsWidespread adoption is critical for organizations to more than double their existing workforce and disrupt traditional work patterns to enable "human-machine collaboration.
I. AI Strategy: The Key Decision for the Future Direction of Enterprises
AI strategies are critical to business success, not just in terms of improving productivity and efficiency, but also in helping organizations design new services, develop market strategies, and catch and correct their own mistakes. Now that AI has the ability to reason independently and understand the impact of decisions, organizations should integrate it into their operational architecture.
Effective AI strategies should take a portfolio approach, including systematic "foundational strategies" to realize small gains, carefully selected and focused investments in achievable "breakthrough strategies," and bold pursuit of high-return but challenging "transformational strategies," such as innovative AI-driven business models. "Transformative strategies, such as innovative AI-driven business models. When selecting big models, organizations should focus more on how they can leverage their own institutional knowledge and proprietary data to leverage the unique benefits of AI, rather than just focusing on the models themselves.
Second, AI Workforce:AI Agents can help companies boost their workforce by 1x
As AI rapidly evolves, the transformation of the AI workforce is becoming a key driver in the transformation of business operating models.The emergence of AI Agents is not leading to a shrinking of the enterprise workforce, as some have feared, but rather, it is introducing a host of new members to the enterprise team, leading to a significant expansion of the workforce and a deep transformation in the way work is done.
AI Agents serve as digital employees with powerful autonomous task execution capabilities. They can efficiently handle daily customer inquiries and enhance the customer service experience with fast and accurate responses; in the field of software development, they can automatically generate the "first draft" of software code, providing developers with a strong starting point and accelerating the development process; and they can also transform human-provided design concepts into concrete prototypes, helping innovative ideas to rapidly landing.
These capabilities allow AI Agents to take on many repetitive, regular tasks, freeing up the time and energy of human employees to focus on more creative, strategic and complex tasks.
Anthony Abbatiello, PwC's Workforce Transformation Leader, believes that, AIAgents will play a revolutionary role in transforming the workforce, combining human creativity with machine efficiency to unlock unprecedented levels of productivity and innovation.
This change will fundamentally reshape the workflow of enterprises. Taking customer service as an example, while manual customer service used to spend a lot of time on answering common questions, AI Agents can instantly respond to customer inquiries and provide initial solutions.
When encountering complex problems, human customer service can use its own experience and professional knowledge to carry out in-depth processing on the basis of the information provided by AI Agents, thus realizing human-machine synergy and improving service efficiency and quality. In terms of product design, human designers can work closely with AI Agents, designers put forward creative concepts, AI Agents use their data processing and analysis capabilities to quickly generate a variety of design solutions, and conduct preliminary screening and optimization. Designers then evaluate and improve the solutions provided by AI Agents according to their own aesthetics and professional judgment, and realize the efficient output of innovative design through multiple iterations.
As AI Agents become more widely used in organizations, the structure of their workforce will change profoundly. The number of knowledge workers, as well as sales, field support, and other positions, could double with the addition of AI Agents. This means that enterprises will usher in new development opportunities in terms of market response speed, quality of customer interaction, and product design innovation. Enterprises will be able to bring their products to the market at a faster pace, better meet the diversified needs of customers and enhance the competitiveness of their products.
However, this change has also created new challenges for organizations. For many organizations, integrating AI Agents into workforce strategies is a huge mindset shift. Organizations will need to create new management roles and responsibilities dedicated to integrating digital workers into their existing workforce systems and monitoring and managing them effectively.
This requires business leaders to actively guide their employees to adapt to new ways of working and change their perceptions of AI so that they understand that AI is a tool to enhance human value, not a threat to replace them.
In the process, the role of HR will also need to be redefined. hR will not only have to manage traditional human employees, but will also have to learn to manage AI Agents. this will include acquiring different skill sets and developing new methods of recruiting, nurturing, and evaluating talent.
For example, when AI takes on most of the basic work, enterprises need to ensure that the talent pool can adapt to the new labor structure by cooperating with universities and other institutions to provide new employees with a training path that leads directly to senior positions. At the same time, enterprises also need to establish a sound management mechanism to balance the deployment cost and ROI of AI Agents, develop indicators to measure the performance of human-machine teams, and carry out rigorous supervision to prevent AI Agents from engaging in unexpected, harmful or non-compliant behavior.
As organizations continue to improve their ability to manage and apply AI Agents.Possible trend of "Agents Center" replacing "Centers of Excellence". Companies may be able to establish AI Agents-based work teams in low-cost regions, taking advantage of local resources to reduce costs. The intellectual property generated in the development of AI Agents and its geographic distribution may provide benefits such as tax incentives for companies.
Although establishing an Agents Center may require a higher initial investment, it is expected to generate a higher ROI in the long run within a few years.The rise of AI Agents brings unprecedented opportunities and challenges for companies, and only by responding proactively will companies be able to take advantage of the new workforce changes.
AI ROI: Depending on Responsible AI Practices
As AI becomes increasingly central to business operations, organizations must take a systematic, transparent approach to ensuring the ongoing value of AI investments and managing risk. Company leaders should actively promote AI governance by implementing comprehensive risk assessments, defining a standardized risk taxonomy, and introducing independent oversight mechanisms, such as internal audit teams or third-party expert assessments.
While U.S. federal regulations are expected to remain flexible, organizations will need to be mindful of the differences in state regulations, particularly in the area of privacy, to ensure compliant operations in different industry contexts, achieve strategic goals and earn a strong ROI.
IV. AI and sustainable development: challenges and opportunities
AI has great potential to accelerate the energy transition and help organizations achieve their sustainability goals, but its energy demand and supply are not yet in balance. Enterprises should strategically deploy AI and optimize how it is used, for example by designing AI interfaces that encourage users to use it efficiently.
AI can help companies automate sustainability data collection and analysis, streamline compliance processes, optimize supply chain sustainability, and quantify the value of low-carbon products. In the long run, increased computing power and renewable energy availability will reduce costs and enable AI to play a greater role in sustainability.
V. Impact of AI on product development: shortening the cycle and improving competitiveness
AI, especially multimodal AI, is revolutionizing product development. Its ability to accelerate design iteration, virtual testing and problem troubleshooting promises to cut product development cycles in half, reduce costs and increase product personalization.
However, many organizations are challenged by skills gaps and need to immediately begin upgrading the data science skills of their engineering teams and recruiting relevant talent. Organizations should also update their technology architecture to support "AI at the edge," drive IT transformation, and reorganize technology teams to adapt to the demands of the AI era.
VI. AI's reshaping of the industry's competitive landscape: industries face different speeds of change
AI will transform all industries, but the pace and focus of change will vary across industries. In the consumer market, enterprises will widely apply AI to improve marketing, supply chain management, financial operations and customer service, and enhance competitiveness through intelligent customer service and dynamic pricing, but some enterprises still need to fill the gap in skills and technology infrastructure. In the financial services sector, AI-native startups and large financial institutions will continue to lead the way in innovation, while others may risk falling behind if they do not accelerate their strategic layout.
The healthcare industry will see accelerated AI adoption in a more flexible regulatory environment, with pharma and medtech companies making breakthroughs in areas such as drug development, and healthcare providers using AI to optimize operations and improve clinical outcomes.
In industrial products, some industry leaders will leverage AI to improve efficiency, accelerate R&D, and shorten time-to-market with high-quality data and standardized processes, while others will need to accelerate technology upgrades and skills enhancements. In the technology, media, and telecom sectors, AI agents will transform software platform requirements and business models, and telcos will enhance their capabilities with hybrid AI solutions.