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The Future of AI in Business

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We are experiencing a new global technological revolution around the use and applications of Artificial Intelligence (AI). But what is the future of AI? In recent months, companies and professionals have taken their first steps in its adoption — and experts say in the imminent future AI will become a transformative force, reshaping business strategies and operations around the world.

“If 2024 was the year of AI’s adoption, 2025 will be the year of its transformation. From the redefinition of automation to the healthcare revolution, AI continues to make great leaps across industries.”*

In this article, we will analyze the impact, challenges and opportunities that the era of AI opens up for the future of companies and their managers. We will also look at the training programs that will successfully help us lead the way in the use of AI, and the AI trends for 2025.

What does the future of AI mean for business?

The future of AI is marked by advances that go beyond basic automation. AI’s ability to interpret data in real time, learn from it and act autonomously is reshaping business models.

Leading companies such as Inditex, Zalando and Amazon are already using the technology to anticipate trends, personalize customer experiences and optimize supply chains.

These AI trends show that the use of tools such as deep learning algorithms and generative AI systems can redefine entire industries, from manufacturing to financial services.

The age of AI and the role of business leaders

In the age of AI, the role of business leaders transcends data-driven decision-making. They must become architects of an ethical and strategic vision, capable of integrating AI into organizational culture so that it benefits both the company and society.

On the other hand, as we pointed out in our article on the characteristics of a good leader, it will also be essential for the manager to be able to communicate effectively, empower teams in the domain of AI and create trust around the use of these tools.

Ultimately, guiding teams in a rapidly evolving technology environment requires the skills to communicate, inspire and manage the transformative potential of AI. In this context, the ability to form and lead multidisciplinary teams will be crucial to create a sustainable positive impact.

Transforming the corporate environment for the future of AI

To thrive in the use of AI in the future, businesses must evolve. This includes a comprehensive review of technological infrastructures, prioritizing systems that can handle large volumes of data and ensuring integration between areas.

It is critical that this transformation of the corporate environment for the future of AI addresses three vital points: specialized leadership, team readiness and responsible AI strategies.

#1 Leadership in the age of AI

Business leaders will play a crucial role in establishing a clear vision of how AI will be used in the company. To this end, it is essential to have technical, strategic and human knowledge and skills, including:

  1. Technical understanding of AI: Mastering basic concepts such as machine learning and algorithm ethics.
  2. Data-driven decision-making: Knowing how to interpret results to drive strategic decisions.
  3. Adaptive leadership skills: Managing technological change by fostering collaboration and resilience.
  4. AI ethics and accountability training: Addressing bias and privacy is a must.
  5. Access to networks of experts: Developers, opinion leaders, engineers, specialized media and more.

Business schools like Esade offer training programs specifically designed to equip leaders with these tools and knowledge. Programs such as Rethinking Business with AI, Artificial Intelligence in Business and the Specialization Program in Business Artificial Intelligence (all taught in Spanish) offer first-class training in AI and are taught in collaboration with experts from companies including IBM.

Additionally, undergraduate degree programs such as the Bachelor of Business Administration & Bachelor in Business and Artificial Intelligence and postgrad programs such as the Master in Business Analytics and Artificial Intelligence are innovative educational approaches that will enable new generations of leaders to embrace AI as early as their university years.

#2 Preparing teams for the shift to AI

The preparation of human talent will be key in the era of AI and the future of business. Teams trained in areas such as data analysis, machine learning and technological change management will be critical to integrating AI effectively. Not only will this boost productivity, but it will also help reduce barriers to technology adoption.

#3 Strategies for a responsible transition to the age of AI

To achieve a successful and responsible transition, the following strategies are advisable:

  1. Promote the ethical use of AI: Implement ethical principles and training programs to prevent bias and ensure a positive impact.
  2. Establish algorithm monitoring and auditing policies: Creating regular audit protocols that assess the accuracy, fairness, and transparency of algorithms is critical. This includes, but is not limited to, using automated tools to identify biases, such as IBM’s AI Fairness 360, and testing in simulated scenarios prior to deployment.
  3. Ensure that the human and social impact of technology is positive: Companies must assess the social impact of technology and reinforce its acceptance through responsible initiatives — such as regularly auditing the models used in recruitment — to ensure they don’t perpetuate discrimination.

Consequences and challenges of AI in companies

While the benefits are numerous, the consequences of AI also pose significant ethical challenges that companies must address proactively. These include risks such as privacy, security and job displacement. A strong strategy will minimize the consequences of AI on companies that prioritize ethics.

#1 AI and privacy

Mass data collection by AI systems can put the privacy of users at risk and, without proper control, can result in unethical surveillance. Businesses must comply with regulations such as the GDPR General Data Protection Regulation to ensure transparency.

#2 Security Risks

Cybersecurity will be a key challenge in the future of AI, with systems vulnerable to attack. Investing in robust protection is crucial for businesses.

#3 Erroneous decision-making

Biases in algorithms or errors in data could lead to incorrect business decisions. Monitoring and auditing systems will be essential to ensure sound decision-making and the implementation of successful strategies

#4 Job displacement

Automation can threaten repetitive jobs: a McKinsey study reveals that between 25 and 35% of work activities could change in the next decade, especially repetitive tasks. This will exacerbate inequalities if the transition is not managed with reskilling policies.

Present and future: what AI is already being used in companies?

Among the main AI tools that are currently being used – and will continue to grow exponentially – are:

  1. ChatGPT, Copilot, Gemini: Generative AI tools like these are used to generate texts, content, images and even write programming code, among other uses. According to McKinsey’s 2024 global survey on AI, 65% of respondents reported that their organizations regularly use generative AI — almost double the number in the previous survey.
  2. Chatbots and virtual assistants: Automated response tools streamline and improve customer service. It is estimated that in 2025 chatbots will handle 70% of customer interactions, improving the experience and introducing efficiencies.
  3. Recommendation systems (AI in e-commerce): Platforms such as Amazon and Netflix have perfected AI algorithms to suggest products or content based on user behavior.
  4. RPA (Robotic Process Automation): Companies like UiPath and Automation Anywhere are leading the way in automating repetitive tasks in areas such as finance, human resources, and logistics.
  5. Predictive analytics: Companies in sectors such as retail or manufacturing use AI to analyze large volumes of data to anticipate demand and prevent supply disruptions.
  6. AI systems in cybersecurity: Tools such as Darktrace and CrowdStrike employ advanced algorithms to detect and mitigate threats in real-time.

What does AI look like in 2025?

If you’re wondering what AI will look like in 2025 and future years, the key will be its ability to integrate into everyday business processes. From advanced technologies such as digital twins or agents to generative intelligence, AI will optimize processes and personalize experiences in ways never before seen. Success will depend on combining these tools with ethical leadership and strategic vision.

“According to consulting firms MacKinsey, Gartner and Forrester, AI agents will become one of the top emerging technology applications by 2025.”*

10 trends in the use of AI in companies for 2025

  1. AI agents: Autonomous systems capable of managing complex tasks, streamlining operations and improving the customer experience. Google has based its new Gemini 2.0 AI model on ‘agents’, confirming that the future of this technology is independence and process automation.
  2. Advanced generative AI: Models such as DALL-E will be common in creative industries and advertising.
  3. Digital twins: Technologies that simulate processes or systems to optimize operations, widely used by large corporations such as Tesla, Siemens and General Electric.
  4. Specialized AI systems: Tools for medical diagnoses or automated legal solutions.
  5. Edge AI: AI processed on local devices that do not need to connect to a data center to function. This allows the devices to make autonomous decisions — very useful in medical or automotive settings.
  6. Ethical data analytics platforms: Technologies that ensure ethical compliance with AI.
  7. Hyper-personalization: AI will allow detailed personalization in sectors such as retail, health and finance, deepening customer engagement and loyalty.
  8. Intelligent automation: Integration into business processes for operational efficiency and decision-making.
  9. Human-AI synergy: Enhanced human capabilities and improved decision-making processes in companies.
  10. Advanced data analytics: Investment into AI will see data analytics grow significantly, with the global market reaching $234.6 billion.

Sectors that will lead the adoption of AI in 2025

1. Banking and finance
Financial institutions are using AI to detect fraud, personalize service offerings and improve customer service through chatbots. Tools such as predictive analytics also optimize investments and manage risks accurately.

2. Health
AI is revolutionizing medical diagnostics by using algorithms that analyze images such as X-rays and MRIs quickly and accurately. It’s also being used in drug research and personalized treatment planning.

3. E-commerce and retail
AI-based recommendation systems help personalize the customer experience. In addition, predictive analytics tools optimize inventory management and logistics in the supply chain.

4. Manufacturing
The adoption of digital twins and robotic automation is optimizing production. This reduces errors and costs, while allowing factories to operate with greater efficiency and flexibility.

5. Energy and sustainability
AI is helping energy companies optimize energy consumption and generation, especially in renewables. It is also used to analyze climate data and improve operational efficiency in sustainable projects.

6. Transport and logistics
Autonomous vehicles, intelligent traffic management systems and route optimization are clear examples of AI’s impact on this sector.

7. Education
Personalized learning platforms and AI-powered virtual tutors are transforming the way students interact with educational content — increasing the accessibility and adaptability of learning.

“Is your company ready to lead this change? Request more information on how to lead the AI revolution with Esade”.*

* Sarah Chudleigh, content writer at the specialized platform Botpress.



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AI agents poised to replace humans as basic unit of a company, Lee Kai-fu says

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Artificial intelligence agents are emerging as an instrument of transformation in the workforce, with the potential to replace humans in traditional roles, according to computer scientist Lee Kai-fu, founder and CEO of the Chinese start-up 01.AI.

“The basic unit of a company will evolve from a human being to an AI agent,” Lee said on Thursday at a summit on disruptive technologies hosted by Swiss bank UBS. AI agents are software apps that use AI to autonomously execute tasks and achieve goals on behalf of users.

Lee pointed out that AI agents could operate around the clock, be replicated infinitely, and scale effortlessly – capabilities unmatched by human workers. “If you have a super employee, you can’t replicate [them], right? Human cloning is not legal, but AI agent cloning is perfectly fine, and they will scale,” he said.

“You can completely use agents as Lego blocks,” he said. “So you have a Lego block that’s [human resources], a Lego block that’s legal, a Lego block that is finance, and then a Lego block for customer service, et cetera.”

“Then you can have a huge, giant Lego-created machinery that is your company agent, where the CEO interacts and manages the company, and that’s what [OpenAI CEO] Sam Altman means when he says there will be US$1 billion companies.”

AI agents are software apps that leverage AI to autonomously perform tasks for users. Photo: Shutterstock Images



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Cisco Supercharges Observability with Agentic AI for Real-Time Business Insights

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Splunk Observability unlocks actionable AI insights to help organizations improve the reliability of their entire digital estate 

 

Today Cisco announced agentic AI-powered Splunk Observability, an AI-native approach to observability that sets a new standard for how customers can strengthen their resilience. The enhanced Splunk Observability portfolio unifies observability across environments, surfaces actionable business context, and deploys AI-powered agents across the full incident response lifecycle, while monitoring both its performance and quality. Through integrations across Cisco technologies with Splunk, customers gain unmatched visibility and correlation of data insights across their networks, infrastructure, and applications to improve the reliability of their entire digital estate.

 

“Our mission is clear – to help organizations put AI applications and agents to work, while retaining visibility and control,” said Patrick Lin, SVP and GM of Splunk Observability. “With the latest innovations in Splunk Observability, we are empowering enterprises to proactively monitor their critical applications and digital services with ease, resolve issues before they escalate, and ensure the value and outcomes they derive from observability are commensurate with the cost.”

 

Agentic AI is reshaping what it takes to build a leading observability practice. As AI-assisted coding gains steam, applications will be built with less human involvement. At the same time, a new wave of AI-enabled applications and AI agents demand specialized telemetry to confirm models are performing as intended – aligned to business purpose and cost. To keep pace, organizations need unified, in-context, visibility across all of these environments to prioritize issues based on business impact.

 

Agentic AI-powered observability: proactive detection, investigation and resolution

Splunk is advancing Cisco’s AgenticOps vision through an enhanced Splunk Observability portfolio, supercharged by new agentic AI innovations. These innovations will deploy AI agents to automate telemetry collection and alert configuration, detect issues, identify root causes, and recommend fixes – freeing ITOps and engineering teams to focus on innovation. These advancements include:

  • AI Troubleshooting Agents: Offered in Splunk Observability Cloud and Splunk AppDynamics, these agentic AI features automatically analyse incidents and surface potential root causes, helping users to quickly act on issues.
  • Event iQ: Offered in Splunk IT Service Intelligence (ITSI), Event iQ helps teams easily set up automated alert correlation to quickly reduce alert noise and gain clear context on grouped alerts.
  • ITSI Episode Summarization: In conjunction with AI-driven alert correlation through Event iQ, Episode Summarization in Splunk ITSI automatically provides overviews of grouped alerts, including trends, impact and root cause, to help troubleshoot faster.

 

Observability for AI to monitor the performance of AI agents, LLMs, and infrastructure 

As organizations integrate AI and large language models (LLMs) into their applications and deploy AI agents, they need specialized analytics to help ensure their AI is behaving as intended. Splunk helps teams proactively monitor the health, security, and cost of their AI application stack, including agents, LLMs, and AI Infrastructure, with:

  • AI Agent Monitoring: Monitors the quality, security, and cost of LLMs and AI agents to determine whether models are performing at the right price and as intended, to align with business goals.
  • AI Infrastructure Monitoring: Proactively monitors the health and consumption of AI infrastructure by alerting on bottlenecks and spikes across services to manage costs.

 

Unified observability that surfaces business and end-user impact

Cisco is bringing the best of Splunk AppDynamics and Splunk Observability Cloud together to provide a unified experience across three-tier and microservices environments, and deepening integration with Cisco ThousandEyes so ITOps, NetOps and Engineering teams can pinpoint the network’s impact on application performance and end-user experience. The innovations include:

  • Business Insights in Splunk Observability Cloud: Teams can correlate application performance with the real-time health of critical business processes, such as checkout, loan processing, and supply chain flows with minimal setup.
  • Digital Experience Analytics in Splunk Observability Cloud: Product and design teams can gain deep visibility into user journeys and behaviour, accessing richer customer experience insights and a faster setup.
  • APM support for hybrid apps and business transactions in Splunk Observability Cloud: These capabilities strengthen APM for cloud-native applications and extend support for hybrid environments—building on Splunk AppDynamics’ expertise in monitoring traditional three-tier applications.
  • Session Replay for Real User Monitoring (RUM) for Splunk AppDynamics and Splunk Observability Cloud: New Browser and Mobile Session Replay in Splunk AppDynamics and Splunk Observability Cloud will help teams optimize online experiences.
  • Splunk AppDynamics Agent: Leveraging OpenTelemetry, this agent enables customers to collect data in either Splunk AppDynamics or Observability Cloud, enabling Splunk AppDynamics customers to use the observability offering that suits their needs.
  • Splunk Observability Cloud Real User Monitoring (RUM) Integration with Cisco ThousandEyes: Users can correlate real-user experience with network performance across owned and third-party domains, to help pinpoint regions or services affected by network bottlenecks.

 

“Through the new agentic AI innovations within Splunk Observability, Cisco offers organizations more proactive visibility and actionable insights into both their digital operations and AI system health and performance,” said Torsten Volk, Principal Analyst, Application Modernization, Enterprise Strategy Group. “These kinds of capabilities are critical as enterprises look to scale AI in a controlled and reliable manner.”

 

Availability:

  • Splunk AI Agent Monitoring, AI Troubleshooting Agents, ITSI Episode Summarization, Business Insights, Digital Experience Analytics, and Splunk RUM Integration with Cisco ThousandEyes are available or will be available soon in Alpha (private preview).
  • All other innovations listed are now generally available to all global regions.

 

For more details on all of Splunk’s .conf25 announcements, please visit our newsroom. Availability dates and regions are subject to change.

 

Many of the products and features mentioned are still in development and will be made available as they are finalized, subject to ongoing evolution in development and innovation. The timeline for their release is subject to change.

 

About Cisco 

Cisco (NASDAQ: CSCO) is the worldwide technology leader that is revolutionizing the way organizations connect and protect in the AI era. For more than 40 years, Cisco has securely connected the world. With its industry leading AI-powered solutions and services, Cisco enables its customers, partners and communities to unlock innovation, enhance productivity and strengthen digital resilience. With purpose at its core, Cisco remains committed to creating a more connected and inclusive future for all. Discover more on The Newsroom and follow us on X at @Cisco.

 

Cisco and the Cisco logo are trademarks or registered trademarks of Cisco and/or its affiliates in the U.S. and other countries. A listing of Cisco’s trademarks can be found at http://www.cisco.com/go/trademarks. Third-party trademarks mentioned are the property of their respective owners. The use of the word ‘partner’ does not imply a partnership relationship between Cisco and any other company.

 

About Splunk LLC

Splunk, a Cisco company, helps build a safer and more resilient digital world. Organizations trust Splunk to prevent security, infrastructure and application issues from becoming major incidents, absorb shocks from digital disruptions, and accelerate digital transformation.

 

Splunk and the Splunk> logo are trademarks or registered trademarks of Cisco and/or its affiliates in the U.S. and other countries. A listing of Cisco’s trademarks can be found at http://www.cisco.com/go/trademarks. Third-party trademarks mentioned are the property of their respective owners. The use of the word “‘partner”’ does not imply a partnership relationship between Cisco or its affiliates and any other company.

 



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Microsoft AI CEO: Giving AI Rights Is ‘Dangerous and Misguided’

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AI systems may feel real, but they don’t deserve rights, said Microsoft’s AI CEO.

Mustafa Suleyman said in an interview with WIRED published Wednesday that the industry needs to be clear that AI is built to serve humans, not to develop independent will or desires.

“If AI has a sort of sense of itself, if it has its own motivations and its own desires and its own goals — that starts to seem like an independent being rather than something that is in service to humans,” he said. “That’s so dangerous and so misguided that we need to take a declarative position against it right now.”

The former DeepMind and Inflection cofounder pushed back against the idea that AI’s increasingly convincing responses amount to genuine consciousness. It’s “mimicry,” he said.

He also said that rights should be tied to the ability to suffer — something biological beings experience but AI does not.

“You could have a model which claims to be aware of its own existence and claims to have a subjective experience, but there is no evidence that it suffers,” he said.

Humans don’t owe them any moral protection or rights. “Turning them off makes no difference, because they don’t actually suffer,” he added.

AI as sentient beings

Suleyman’s comments come as some AI companies explore the opposite: whether AI deserves to be treated more like sentient beings.

Anthropic has gone further than most companies in treating AI systems as if their welfare matters. The company has hired a researcher, Kyle Fish, whose role is to consider whether advanced AI might one day be “worthy of moral consideration.”

His job involves exploring what capabilities an AI system would need before earning such protection, and what practical steps companies could take to safeguard the “interests” of AI, Anthropic told Business Insider last year.

Anthropic has also recently experimented with how to end extreme conversations — including child exploitation requests — in ways that extend “welfare” considerations to the AI itself.

In April, a principal scientist at Google DeepMind said the industry might need to rethink the concept of AI consciousness altogether.

“Maybe we need to bend or break the vocabulary of consciousness to fit these new systems,” Murray Shanahan said on a Deepmind podcast published in April. “You can’t be in the world with them like you can with a dog or an octopus — but that doesn’t mean there’s nothing there.”

Suleyman previously said that there is no evidence that AI is conscious.

In a personal essay published last month, he wrote that he was “growing more and more concerned” about so-called AI psychosis, a term increasingly being used to describe when people form delusional beliefs after interacting with chatbots.

Suleyman and Microsoft did not respond to a request for comment from Business Insider.





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