With many companies looking for stronger safeguards after recent internet disruptions exposed weaknesses in single-cloud setups, the launch comes just in time.

Both firms said the service allows customers to build secure, high-capacity connections between Amazon Web Services (AWS) and Google Cloud in minutes. Before now, many organisations waited weeks to complete the same process due to the technical and approval delays tied to cross-cloud circuits.

Just over a month ago, AWS suffered a major outage on October 20 that spread through its US-East-1 region. A faulty update to DynamoDB’s API triggered DNS failures across the zone, breaking more than 113 AWS services and knocking out platforms such as Snapchat, Reddit, Coinbase and Alexa. 

Analysts estimate the disruption costs U.S. companies between $500 million and $650 million. For many firms, the incident revealed the risk of placing all operations on a single cloud provider.

In response, interest in multicloud resilience has grown. The new service blends AWS’ Interconnect–multicloud with Google Cloud’s Cross-Cloud Interconnect. The aim is to remove friction for organisations that want systems running across several clouds without slow setup cycles or unpredictable routing.

AWS vice president of network services, Robert Kennedy, said the development points to a major shift in how cloud platforms interact. “This collaboration between AWS and Google Cloud represents a fundamental shift in multicloud connectivity.”

Google Cloud also noted the benefit for companies moving large volumes of data between providers. Its vice president and general manager of cloud networking, Rob Enns, stated that the joint framework is meant to simplify workload mobility. Salesforce is one of the early adopters of the new model, according to Google.

Cloud competition is highly intense. AWS continues to top the global market with roughly 29–30% share, while Microsoft Azure holds about 20% and Google Cloud has climbed toward 13%. 

In the third quarter alone, the cloud infrastructure market was valued at around $107 billion, controlled largely by these three companies.

Heavy investment in infrastructure is expected to continue. Increasing demand for artificial intelligence is pushing cloud providers to expand data centres, improve capacity and strengthen network routes. 

AWS recently committed to a multi-year $38 billion partnership with OpenAI, offering access to large clusters of Nvidia GPUs. Google and Microsoft are making similar bets, as AI workloads remain one of the biggest drivers of cloud growth.

In working together on a cross-cloud standard, Amazon and Google have taken an unusual step. The two companies are long-standing competitors, but the new partnership shows a shared interest in reducing latency and making multicloud operations easier for enterprise customers. 

For large users like Salesforce, the ability to deploy cross-cloud links in minutes rather than weeks may prove decisive as businesses seek more resilient infrastructure after recent outages.

In Africa, approximately 40% of organisations are either experimenting with or deploying generative AI tools.

This adoption is already yielding measurable success: 51% of South African businesses believe generative AI has improved productivity and competitiveness.

Governance: The foundation for reliable innovation

To ensure this growth is reliable and responsible, organisations must build a foundation of trust. AI runs on data, and data runs on trust. Building a healthy data culture involves knowing what information is held, where it lives, who can use it, and for what purpose.

This is where governance comes in, providing structure and discipline. Governance establishes the standards and controls necessary to ensure information accuracy and security, as well as the accountability to uphold them.

Crucially, when governance works as it should, it doesn’t slow innovation – it makes it safer and faster. Clear rules give businesses the confidence to move quickly, use data creatively, and make better decisions.

African nations are proactively establishing strong legal foundations for trust in the digital space. For instance, South Africa mandates that boards are held responsible for managing data risk and ensuring lawful usage through its  Protection of Personal Information Act (POPIA) and the King IV Code. Similarly,  Nigeria’s Data Protection Act demands essential principles like transparency, consent, and human oversight in data handling. Meanwhile, in Kenya, the Ministry of Information, Communications and the Digital Economy (MICDE) is the primary governmental body actively driving cybersecurity and AI governance efforts.

Strategic security for sustainable growth

Africa’s AI market is projected for significant expansion, expected to reach around $6.4 billion by the end of 2025, supported by more than 2,400 AI-focused companies. This growth won’t be sustainable without strong foundations.

While the technology that makes work smarter can also be used by cybercriminals (e.g., forging images or cloning voices), organisations are implementing strategic solutions to mitigate these risks. Boards and executives must look at information governance as a strategic priority, not merely a technical one.

Technology offers robust support for this strategic focus: platforms can automate data protection, monitor activity, and simplify compliance, helping with the heavy lifting of security.

Empowering the human element

Cybersecurity, data governance, and training must all work together to maintain a secure system. Employees are essential, remaining the first and last line of defence.

Top down organisational culture is key to empowering employees with necessary skills. These essential skills include recognising manipulated voices, spotting deepfakes, avoiding suspicious links, and questioning urgent payment requests.

The safest way to work with AI is to treat data with the same care afforded to money or reputation. By integrating rules, oversight, and discipline, organisations keep the system honest.

The principle guiding this growth remains clear: progress is nothing without trust.

Announced ahead of its flagship Dreamforce 2025 conference, set to begin on October 14, Agentforce 360 introduces new features designed to make AI agents more responsive, adaptable, and integrated into daily enterprise workflows. 

The update includes tools that allow users to build, test, and deploy AI agents with greater control and flexibility.

One of the features is Agent Script, a prompting tool that lets users instruct AI agents through conditional “if/then” logic. The tool, set for beta release in November, gives companies the ability to improve how agents respond in nuanced or unpredictable situations, such as complex customer queries. 

According to Salesforce, these agents will use “reasoning” models powered by Anthropic, OpenAI, and Google Gemini, which “think before responding” rather than relying solely on pattern-based outputs.

Another addition is Agentforce Builder, a unified workspace where users can create, test, and launch AI agents from a single interface. The platform also includes Agentforce Vibes, a customisation framework for defining the tone and “personality” of enterprise applications. Both features are expected to enter beta testing in November.

Salesforce is also expanding its integration with Slack, placing the workplace platform as a hub for enterprise intelligence. Starting this month, Salesforce’s core applications, including Sales, IT, and HR, will become accessible directly within Slack, with further expansion planned through early 2026. 

A new version of Slackbot is being piloted as well, designed to act as a personal assistant that learns user preferences and offers proactive insights and suggestions.

The company’s long-term plan is to make Slack a full-scale enterprise search and collaboration tool, connecting it with external platforms like Gmail, Outlook, and Dropbox by 2026.

Salesforce says it currently serves 12,000 Agentforce customers, including early adopters such as Lennar, Adecco, and Pearson. 

Salesforce’s innovation could be a huge one for businesses still having issues with measurable returns from their AI investments. A recent MIT study found that 95% of enterprise AI pilots fail before reaching production, emphasising the challenges companies face in scaling these technologies effectively.

Competitors are also moving quickly. Google recently launched Gemini Enterprise, with clients like Figma and Klarna, while Anthropic secured a major deal with Deloitte to roll out its Claude Enterprise chatbot to 500,000 employees and later announced a partnership with IBM. Unveiling Agentforce 360 just before Dreamforce, Salesforce aims to showcase incremental updates, but has a bigger vision for how enterprise AI should function, integrated, adaptable, and built for long-term scalability.

The data is compelling – according to the World Bank’s recent Global Economic Prospects report, rising global trade and policy uncertainty could weaken growth by 2.3% in 2025, impacting both major economies and emerging markets.

In the face of these headwinds, many businesses are ramping up plans to implement AI, driving new levels of productivity and cost savings. In a March 2025 survey by McKinsey, 78% of respondents reported their organisation already uses AI in at least one business function, up from 72% in early 2024 and 55% a year earlier.

Put simply, AI is the most transformative technology of our lifetime. Its latest iteration, agentic AI—always-on intelligent agents that can learn, reason, and execute tasks independently – will reshape how companies operate, compete, and perform work.

While this new era holds great promise, the journey to becoming an agentic enterprise can feel daunting.

Aligning your business with a tangible agentic AI strategy, readying your technology infrastructure, and understanding the metrics that define success are essential pillars to unlocking the agentic AI opportunity and realising the return on investment (ROI) this moment demands.

Realise trapped value with automation and augmentation

Nearly half of desk workers report spending time on repetitive, low-value, or unrelated tasks to the jobs they were hired to do. Across many industries, operational inefficiencies and unrecognised opportunities are buried deep within data, processes, and human workflows, affecting everything from employee engagement to the bottom line.

The first step to reigniting productivity growth is identifying what’s holding organisations back and finding solutions to these challenges, known as trapped value analysis.

Start by identifying where high-value, underperforming workflows exist. For example, are there manual tasks slowing teams down? Can they be automated? Which customer interactions can be more personalised?

Augmenting human capacity with a digital workforce is key to realising trapped value, enabling smarter, faster decision-making grounded in trusted data and improving personalised customer interactions at scale.

Imagine a marketer at a young company suddenly supported by a team of AI agents to strategise, plan, and deliver best-in-class campaigns. Or a sales rep with instant access to real-time customer data analysis and predictions of which leads are most likely to convert.

Deploying AI agents isn’t about replacing people; it’s about empowering employees to focus on what they do best – strategic thinking, innovating, and building relationships with customers.

Overcoming productivity pain points with a dynamic IT infrastructure powered by digital labour allows businesses to reprioritise their newly available human capacity to where it can have the greatest impact. This is key to realising new revenue streams or business models and is fundamental to unlocking ROI.

Set critical metrics to measure ROI

The advantages of digital labour for optimising operations are clear. However, according to Gartner, over 40% of agentic AI projects will be cancelled by the end of 2027 due to reasons such as unclear business value.

To demonstrate real ROI, organisations need to focus on enterprise productivity, driving business value through quality, cost, speed, and scale.

For customer service teams, measuring ROI can involve assessing customer satisfaction, such as improving experiences with 24/7 support across channels where AI agents triage requests and provide step-by-step instructions using natural responses.

When Salesforce added Agentforce to its Help site in October 2024, the goal was to set a world-class standard for agentic service.

With an AI agent answering customer service questions in natural language, using unified data to provide fast, 24/7 support, our human engineers can focus on complex issues.

To date, Agentforce has handled over 1 million support requests and is projected to save $50 million annually by the end of this fiscal year.

For sales teams, ROI can be seen in faster response times and increased lead qualification. Agentic AI enables scaling with autonomous outreach to answer product questions, handle objections, and book meetings, interacting with customers across relevant channels with personalised responses.

All of these efficiency gains free up time for humans to focus on improving and driving growth in other areas of the business.

Using metrics – from deflection rates to customer satisfaction scores and operational savings — enables organisations to assess the performance of their AI agent initiatives and calculate ROI effectively.

Access long-term value

By focusing on these metrics, African businesses can effectively assess the performance of their AI initiatives and calculate ROI, moving from a position of uncertainty to one of strategic growth.

In essence, the agentic AI era is not about a single, abrupt change but a fundamental shift in how people and technology work together.

By embracing a phased, strategic approach, African businesses can navigate this transition successfully, accelerate productivity, and ultimately unlock significant long-term value. This is the new partnership that will enable businesses to thrive amid today’s challenges.

This new class of digital labour is changing how teams function, how targets are met, and how people spend their time at work.

From now on, almost every job, team, and company will involve AI agents – systems that can analyse vast datasets, apply human-like reasoning, and act independently.

Their presence is set to influence workflows, increase productivity, support innovation, and redefine roles across the organisation.

Rather than replacing people, AI is tilting the workload. Salesforce research shows that 23% of HR teams plan to redeploy employees into roles that make better use of their uniquely human strengths. At the same time, agentic AI adoption is projected to surge by 327% over the next two years (from roughly 15% adoption today to about 64% by 2027).

This shift is tied to anticipated productivity gains of 30% per employee and labour cost reductions of 19%, equating to about $11,000 in savings per employee annually, based on Organisation for Economic Co-operation and Development (OECD) wage averages. Rather than replacing people, organisations are preparing to reskill and redeploy workers, enabling humans to focus on higher-value roles that emphasise creativity, strategy, and interpersonal skills.

A recent Gartner poll further found that 95% of customer service teams intend to retain human agents to help define and guide the role of AI, reinforcing the value of a “digital first, not digital only” approach.

Gartner further says that by 2027, half of the organisations that planned to significantly reduce their customer service workforce will abandon those plans, highlighting the limits of going fully “agentless”.

For African countries, the rise of digital labour presents an opportunity to build modern, inclusive workforces without being bound by outdated development models.

But realising this potential depends on sustained investment in skills training, digital infrastructure, and equitable access to AI tools.

Train for tomorrow

Africa has the world’s youngest population. It’s bursting with entrepreneurial energy. But many young people still don’t have access to the tools and skills that will define the next era of work.

If the continent wants to lead in the digital labour revolution, it should act now by investing in digital infrastructure, prioritising skills development, and forging partnerships that make future-focused training widely accessible.

Yes, the skills gap is real and broadband internet is still a luxury in many communities. But on the upside, AI training doesn’t require a university degree. Much of it is free, online, and accessible to anyone with a smartphone and a curious mind.

That opens the door to governments, educators, businesses, and civil society to step up to update school curricula, expand digital infrastructure, and support public-private training partnerships. All of this matters: not just for economic growth, but for social inclusion, too.

If these foundations are put in place, African countries could not only meet the needs of their growing population but also leapfrog outdated development models.

From entry-level to in-demand

When AI begins to handle the simpler tasks, it’s easy to worry about what’s left for those starting out. Entry-level jobs aren’t disappearing though.

Instead of doing routine work, newcomers will now need to build skills in oversight, collaboration, and using AI tools effectively from day one. The ladder still exists; it just starts in a different place.

This will require a different kind of training – not just technical know-how, but in soft skills like empathy, adaptability, ethical judgement, and communication, which are all human traits that help teams thrive.

AI’s presence in the workplace may be concerning, with reports of job cuts due to its adoption (here, here, here, and here), but all is not as it seems.

Research suggests a more balanced perspective: One of the most comprehensive studies, from the National Bureau of Economic Research, tracked 25,000 workers across 7,000 Danish firms using AI chatbots. It found no significant changes to jobs, wages, or working hours. Productivity rose by around 3%, without leading to layoffs.

The St. Louis Fed found something similar. Based on large-scale surveys in the US, researchers reported one in four workers now use generative AI weekly, saving on average just over two hours a week. Spread across the entire labour market, that translated into a 1.1% productivity gain. Crucially, there was no sign this efficiency came at the cost of jobs.

Adding to this, a 2024 study by Mäkelä and Stephany analysed over 12 million US job listings and revealed that demand is surging for “AI-complementary” skills such as resilience, teamwork, digital literacy, and analytical thinking.

These are the very human capabilities that help people work effectively with AI. The study found AI-focused roles are nearly twice as likely to list these skills, and they command wage premiums of 5–10%.

Even more telling: the positive impact of these complementary skills outweighs the substitution effects of AI by up to 70%.

These findings all suggest that AI isn’t replacing workers; it’s helping them work smarter and more efficiently.

To thrive in this blended future, we need to prepare today, by building the right skills, expanding access, and embracing AI not as a threat, but as a partner in progress.

Because the future of work won’t be entirely human, nor entirely automated – it will be a blend of both.

Organisations today face a data paradox: they need to make fast, intelligent decisions but are overwhelmed by large volumes of often unreliable information.

With over 75% of business leaders under pressure to prove data’s value, the demand for trusted, actionable insights has never been greater.

Salesforce’s Tableau Next introduces a new approach to business intelligence, evolving its flagship analytics platform with agentic analytics to address this challenge.

This innovative, AI-powered solution simplifies and accelerates data interaction, empowering organisations to uncover insights, automate visualizations, and drive impactful business outcomes.

What is agentic analytics

Agentic analytics allows users to collaborate with AI agents to speed up the entire data-to-action process. Instead of relying on static visualizations, analysts can use AI to automate tasks like data preparation and ETL (extract, transform, load processes), freeing them to focus on deeper analysis.

Business leaders can ask natural language questions and get instant, reliable answers along with recommended actions. This makes data-driven decision-making easier and more efficient, removing the need for technical expertise and manual effort typical of traditional BI tools.

Tableau Next leverages agentic analytics across the entire data-to-action workflow, empowering every user to:

• Automate repetitive data tasks like data cleaning, transformation, and visualization generation, as well as the execution of complex, multi-step analytical workflows within and across different business areas. This builds on Tableau’s strength in simplifying complex data for users.
• Proactively deliver faster, more comprehensive insights by autonomously detecting hidden correlations, outliers, and trends that might be missed by human observation. This enhances Tableau’s focus on user-driven insights by providing AI guidance.
• Enable more contextual and effective action through natural language summaries, visualisations, and data-driven recommendations, insights delivered where people work with an enterprise-class workflow engine that enables users to kick off automated actions. This extends Tableau’s ability to drive action from data, making it more seamless within the Salesforce ecosystem.

How Tableau Next works:

Built on the trusted Salesforce Platform and leveraging the power of Data Cloud, Tableau Next delivers enterprise-grade performance, robust security, and flexible, zero-copy data integration for seamless data connectivity.

Tableau Semantics, an intelligent semantic layer, provides a unified understanding of information, ensuring data consistency and accelerating the discovery of critical insights.

The built-in workflow engine in Tableau Next seamlessly translates insights directly into actionable steps, dramatically accelerating the time to value.

The key differentiator is the native integration with Agentforce, Tableau Next equips humans and AI agents with pre-built analytical skills to rapidly transform data into tangible business value, marking a significant leap forward in data-driven decision-making. It includes:

Agentic AI Skills to Supercharge Your Data:

• Data Pro: Your Intelligent Data Prep Assistant. Instead of users manually cleaning up and changing data using complex steps (like in traditional ETL), Data Pro will give smart suggestions on how to do it and even automatically handle some of the complicated changes, saving time and effort.
• Concierge: Instant Answers in Plain Language. Get immediate, reliable answers to data questions. Sales teams, for example, can simply ask “What are my best sales opportunities?” and receive clear insights with recommended actions.
• Inspector: Proactive Data Monitoring & Insights. Continuously tracks your data for key changes, analyzes trends, and predicts improvements. Service teams can be instantly alerted to drops in customer satisfaction, enabling immediate action.

Ensuring Data Trust and Accuracy:

• Tableau Semantics: Tableau Semantics serves as the semantic layer, providing Tableau Next and Agentforce with a unified understanding of business data. By establishing consistent definitions and context, it enables AI agents to generate accurate and relevant responses.

Boosting Efficiency:

• Marketplace: Allows users to easily share and reuse data analysis components (like data assets, connections, metrics, visualizations, dashboards), saving time and ensuring everyone is working with the same information.

“Tableau Next helps businesses achieve faster, more impactful results with their data,” said Ryan Aytay, CEO of Tableau. “We’re shifting from basic reports to a world where AI is a collaborative decision-making partner. By combining AI agents with trusted data and easy-to-use tools, we’re making data accessible to everyone and transforming the data-to-action process into an automated, proactive, and insight-driven cycle. This empowers users to improve decision-making, boost efficiency, and manage risk more effectively.”

Linda Saunders, country manager and senior director of Solution Engineering for Africa said: “Among the biggest benefits of agentic AI solutions will be on-demand, instant access to personalise financial recommendations that may otherwise require appointments and taking time out of busy schedules.”

In addition to taking the pulse of consumers’ sense of financial security and goals, the report delves into how customer experiences — including those increasingly powered by artificial intelligence (AI) agents — are changing individuals’ relationships with their FSIs.

“For humans and agents to work together, it’s critical for financial service institutions to implement with trust, transparency, and the highest levels of regulatory compliance as core to their strategy — not an afterthought,” adds Saunders.

Key insights from the research include:

• Differentiated service and experience can outweigh rates and fees. 45% would stay with a provider that offers excellent service, even if fees increased. This is especially true for 56% of high earners.
• Consumers have big expectations for AI in financial service: 43% of FSIs in EMEA, including 54% of Gen Z and 50% of millennials, expect AI to play a bigger role in financial services than in other industries. FSIs are most interested in use cases that prevent fraud, lower prices, and complete routine tasks.
• Building trust is essential as agentic AI is rolled out: 49% of consumers at least somewhat trust the use of AI agents in financial services, but only 8% are fully on board. The top factors that would build consumers’ trust in AI agents are transparency into their use, validation of their outputs, and explainability of their outputs.

Constituents around the world agree there’s room for improvement when it comes to government service.

Forty percent struggle with government interactions, and over a third are unsure of available programs.

However, the research indicates overwhelming public support for AI solutions — with 90% of global constituents saying they’d use an AI agent to engage with their government.

The arrival of AI agents presents governments with an exciting opportunity to strengthen public trust by streamlining services and speeding up response times.

And in the face of tightening budgets, agents can augment public servants and better serve their constituents — without having to add headcount.

“It is clear from our research that there is a need for AI solutions like Salesforce’s Agentforce that help governments streamline and scale services to better meet the needs of their constituents,” said Nasi Jazayeri, EVP and GM of Public Sector at Salesforce. “As global leaders gather in Davos, we have a tremendous opportunity for the public and private sectors to come together and explore how major advancements in technology like AI agents can improve how governments support citizens.”

Key Highlights:

• 40% say it’s difficult to interact with the government when they have questions or need help.
• Less than half of survey respondents find it easy to understand what public services (42%) and public assistance programs (46%) are available to them.
• Top service delivery improvements desired by global constituents include:
  • Reducing the number of steps to address needs
  • Responding to their needs faster

Constituents eager to engage with agents

• 90% of global respondents said they’d use an AI agent to interact with the public sector.
• Constituents in Brazil, Spain, Singapore, and Italy are among the most willing to use AI agents to interact with the public sector, providing these countries with the opportunity to be trailblazers in the agentic AI era.
• 20% of German and American respondents say they’re very likely to use an AI agent to help fill out government forms (e.g. filing taxes, completing applications).
• Three factors global respondents said they prioritised when considering using AI agents in the public sector:
  • 24/7 access to information and services (47%)
  • Helping them efficiently access government resources (44%)
  • Reducing the number of websites and steps needed to address their needs (40%)

The report indicates that the better-than-expected holiday shopping season was powered by surges in mobile and social commerce alongside increased consumer spending after months of saving in the first half of 2024. However, shoppers have already sent back $122 billion in merchandise.

Both consumers and retailers leaned into the use of AI and agents to enhance holiday shopping experiences through product recommendations and personalised order support, influencing $229 billion – or 19% – of all online orders.

“Retailers had a robust holiday season, but a 28% rise in the rate of returns compared to last year is a cause for some concern,” said Caila Schwartz, director of Consumer Insights at Salesforce. “Retailers who have embraced AI and agents are already seeing the benefits, but these tools will be even more critical in the new year as retailers aim to minimise revenue losses on returns and reengage with shoppers.”

Salesforce data, based on an analysis of 1.5 billion shoppers and 1.6 trillion page views across the Salesforce Platform, highlights trends that shaped the holiday season, including:

Online sales and order growth reached new peaks: 

• Online sales reached $1.2 trillion globally and $282 billion in the U.S. This represents a 3% global year-over-year (YoY) increase and a 4% YoY increase in the U.S. Online sales also grew 1% YoY in the European Union (EU).

Retailers harnessed the value of AI and agents:

• $229 billion of global online sales were influenced by AI and agents in the form of product recommendations, targeted offers, and conversational customer service support.
• 19% of holiday purchases were influenced by consumers engaging with AI and agents, a 6% increase from 2023.
• Retail use of generative AI features like agents increased 25% during the holiday season compared to September and October in 2024.
• Shoppers used AI- and agent-powered chat for customer service 42% more than they did during the 2023 holiday season.

The rate of returns rapidly increased:

• More than $122 billion of global purchases have already been returned, up 28% from last year.
• This increase is partially due to trending consumer behaviors like “try-on hauls” and bracketing (buying an extra size above and below your standard size).
• Salesforce projects that retailers will likely see this number grow to $133 billion – presenting an important opportunity for brands to use agents to make the returns process easier and more tailored to specific customer needs.

Social commerce grew its influence on shoppers:

• Retailers using social commerce strategies saw 20% of global holiday sales generated through platforms like TikTok Shop and Instagram.
• Social media as a traffic-referring channel also grew 8% YoY, driving 14% of all traffic to ecommerce sites during the season.

This came after the company exceeded quarterly sales expectations and issued an optimistic forecast for its recently launched AI-driven products, with its stock already up 26% this year.

The product, Agentforce, has become a driver of Salesforce’s growth projections. This innovative tool aims to meet the increasing demand for AI agents capable of performing tasks autonomously. 

Even with its general availability being announced only in late October, Agentforce has already secured 200 deals, with executives highlighting a solid pipeline of future opportunities during a post-earnings call.

Analysts at Piper Sandler described fiscal 2026 as a good year for Salesforce, noting its efforts to enhance enterprise AI through new pricing and packaging models for products such as Agentforce, Foundations, and Data Cloud. 

They anticipate that these offerings will boost the company’s market reach significantly. J.P. Morgan analysts confirmed this but acknowledged that full monetisation could take time.

The company’s market valuation, currently at $316.85 billion, is set to increase by more than $40 billion if the stock maintains its upward growth. Data from LSEG reveal that at least 20 analysts have raised their price targets for Salesforce, with a new median target of $380 suggesting a possible 15% upside.

For the fiscal year 2025, Salesforce has slightly revised its revenue expectations to a range of $37.8 billion to $38 billion, up from its earlier forecast. In the third quarter, the company reported an 8% increase in revenue, reaching $9.44 billion and surpassing analysts’ average estimate of $9.35 billion.

Baird Equity Research analysts commended the company’s progress in integrating AI into its strategy, with reasonable market expectations, and probable gains as enterprise spending recovers.