AlphaFold 3 predicts the structure and interactions of all of life’s molecules - Related to years, life’s, but, their, embracing

93% of IT leaders will implement AI agents in the next two years

Businesses are seeing greater adoption of agentic AI, enhancing their ability to deliver greater value at the speed of need by leveraging digital labor across all lines of business.

, 93% of IT leaders study intentions to introduce autonomous AI agents within the next two years, and nearly half have already done so.

Also: AI agents will match 'good mid-level' engineers this year, says Mark Zuckerberg.

MuleSoft's 10th annual Connectivity Benchmark study is based on survey data from interviews with 1,050 IT leaders across the globe. Here is the executive summary:

Data is trapped across siloed enterprise apps: The average number of apps used by respondents is 897, with 45% reporting using 1,000 applications or more -- further hindering IT teams' ability to build a unified experience. Only 29% of enterprise apps are integrated and share information across the business.

The average number of apps used by respondents is 897, with 45% reporting using 1,000 applications or more -- further hindering IT teams' ability to build a unified experience. Only 29% of enterprise apps are integrated and share information across the business. IT workload is increasing: With IT leaders being pushed to incorporate AI, 86% of respondents anticipate their teams' workload will rise in the next year, all while still maintaining existing systems, including 70% who findings governing enterprise-wide automations.

With IT leaders being pushed to incorporate AI, 86% of respondents anticipate their teams' workload will rise in the next year, all while still maintaining existing systems, including 70% who analysis governing enterprise-wide automations. Integrated user experience is elusive: Enterprise-wide automation is on the rise; even so, 66% of respondents still don't provide an integrated user experience across their channels.

Enterprise-wide automation is on the rise; even so, 66% of respondents still don't provide an integrated user experience across their channels. Integration is a challenge for accelerated adoption of AI agents: Nearly all (95%) of IT leaders investigation 95% integration as a hurdle to implementing AI effectively, but APIs have helped. Fifty-five percent of IT leaders investigation APIs improve their IT infrastructure, while 45% recognize the ability for APIs to support enhancing user experiences.

93% of IT leaders study intentions to introduce autonomous AI agents within the next 2 years, and nearly half have already done so. MuleSoft, Salesforce.

Here are my top 20 big takeaways that every CIO and IT leader must review and self-assess from the findings:

Adoption of autonomous agents is a key business priority: Introducing autonomous agents within the next two years is on the roadmap for 93% of IT leaders; nearly half have already done so.

Introducing autonomous agents within the next two years is on the roadmap for 93% of IT leaders; nearly half have already done so. Productivity gains drive agent adoption: The vast majority (93%) feel that AI will increase developer productivity over the next three years, which is up seven percentage points since last year's investigation.

The vast majority (93%) feel that AI will increase developer productivity over the next three years, which is up seven percentage points since last year's study. More AI models will be deployed to drive agent adoption: The average number of AI models estimated to be used doubled from 2024 (9 to 18), and IT leaders predict a further increase of 78% in the next three years to an average of 32 models.

The average number of AI models estimated to be used doubled from 2024 (9 to 18), and IT leaders predict a further increase of 78% in the next three years to an average of 32 models. IT budgets are growing in 2025: As demand for AI grows, so does the budget: 85% of IT decision-makers expect an increase in their overall budget in 2025, while 11% anticipate that their IT budgets will stay the same.

As demand for AI grows, so does the budget: 85% of IT decision-makers expect an increase in their overall budget in 2025, while 11% anticipate that their IT budgets will stay the same. Investments in data infrastructure are 4X AI investments: To prepare for the expanded use of AI, enterprise CIOs are allocating 25% of their budgets to data infrastructure and management (compared to 5% to AI).

To prepare for the expanded use of AI, enterprise CIOs are allocating 25% of their budgets to data infrastructure and management (compared to 5% to AI). IT workload will increase significantly in 2025: Along with an increased budget, 86% of IT leaders anticipate workloads to rise as well. On average, they expect an 18% increase in the number of projects their organization will need to deliver. To meet this growing demand, IT staffing budgets are also set to rise significantly, with an expected increase of [website] compared to last year's predicted amount, with an estimated budget nearing $17M ($[website].

Along with an increased budget, 86% of IT leaders anticipate workloads to rise as well. On average, they expect an 18% increase in the number of projects their organization will need to deliver. To meet this growing demand, IT staffing budgets are also set to rise significantly, with an expected increase of [website] compared to last year's predicted amount, with an estimated budget nearing $17M ($[website] Project delivery capabilities will decline due to higher demand from IT : The percentage of projects not being delivered on time has risen to 29% from 26% last year. Can AI help? This is one area in which IT leaders are highly optimistic about AI's potential to boost productivity, with 93% expecting it to enhance developer productivity over the next three years, up from 85% in last year's survey.

: The percentage of projects not being delivered on time has risen to 29% from 26% last year. Can AI help? This is one area in which IT leaders are highly optimistic about AI's potential to boost productivity, with 93% expecting it to enhance developer productivity over the next three years, up from 85% in last year's survey. The primary obstacle to AI implementation -- integration and legacy debt: Integration remains the most significant barrier to AI implementation, with 95% of organizations facing challenges when integrating AI into their existing processes. Cybersecurity and data privacy are paramount concerns for IT leaders during AI integration.

Adoption of AI surpass projections MuleSoft, Salesforce.

Disconnected data remains an overwhelming blocker to legacy modernization for the majority of organizations: Today, 83% of organizations study that integration challenges are a significant barrier to their legacy modernization efforts. And 97% of IT leaders acknowledge that their organizations struggle with integrating end-user experiences.

Today, 83% of organizations study that integration challenges are a significant barrier to their legacy modernization efforts. And 97% of IT leaders acknowledge that their organizations struggle with integrating end-user experiences. User experience across all channels is not managed: Around two-thirds (66%) of respondents don't provide an integrated user experience across all of their channels.Integration challenges prevent optimal user experiences -- Integration challenges are hindering digital transformation at their organization for 83% of respondents.

Around two-thirds (66%) of respondents don't provide an integrated user experience across all of their channels.Integration challenges prevent optimal user experiences -- Integration challenges are hindering digital transformation at their organization for 83% of respondents. Connections are key to improved experiences: Around half (49%) findings improved return on investment when creating a connected end-user experience.

Around half (49%) research improved return on investment when creating a connected end-user experience. The top challenges to providing a seamless customer experience are: 1. adopting AI tools (44%), 2. reusing software components to create new products and services (42%), 3. leveraging APIs (37%), 4. implementing microservice architecture (36%), and 5. adopting event-driven APIs (35%).

Disconnected data strains IT resources MuleSoft, Salesforce.

Rising demand for AI agents fuel the need for robust integration.

The number of apps in the enterprise is growing: Organizations are leveraging a staggering number of applications, with an average of 897. Remarkably, 46% of these organizations findings using 1,000 applications or more. Concerningly, only 2% of IT leaders findings their organizations have integrated more than half of their applications.

Organizations are leveraging a staggering number of applications, with an average of 897. Remarkably, 46% of these organizations research using 1,000 applications or more. Concerningly, only 2% of IT leaders research their organizations have integrated more than half of their applications. Customer experiences are mostly digital: With an estimated 71% of all customer engagements occurring in a digital format, the need for application integration is key to success.

With an estimated 71% of all customer engagements occurring in a digital format, the need for application integration is key to success. Data silos are innovation roadblocks: Only 10% of respondents research experiencing no challenges due to data silos, while 74% of organizations find their IT systems to be overly interdependent.

Only 10% of respondents findings experiencing no challenges due to data silos, while 74% of organizations find their IT systems to be overly interdependent. Data mobility is the biggest integration challenge: Moving data from source systems to the data warehouse is the top challenge, followed by correlating data in the warehouse to deliver insights and reusing data information across different user-facing applications.

Moving data from source systems to the data warehouse is the top challenge, followed by correlating data in the warehouse to deliver insights and reusing data reports across different user-facing applications. IT sees a rising need for integration across all departments: , at least 80% or more of data science, engineering, sales, and customer service departments are reporting a need for integration.

, at least 80% or more of data science, engineering, sales, and customer service departments are reporting a need for integration. IT teams face new hurdle with widespread AI: A vast majority (81%) of IT leaders investigation that their companies are grappling with challenges in leveraging AI for system integrations. The average application lifetime within organizations is five years, highlighting the need for robust and adaptable systems that can integrate new technologies -- without compromising performance or security.

A vast majority (81%) of IT leaders investigation that their companies are grappling with challenges in leveraging AI for system integrations. The average application lifetime within organizations is five years, highlighting the need for robust and adaptable systems that can integrate new technologies -- without compromising performance or security. AI needs data to deliver results: Without integration, AI does not have access to the critical data for it to function at its best. Eighty-one percent of respondents identified data integration as one of the most significant challenges their organizations face when implementing AI for systems integrations. Outdated infrastructure is a significant obstacle, with 41% of participants reporting that their organization's old IT architecture and infrastructure hinder the use of data for AI applications.

Rising AI demand fuels the need for robust integration MuleSoft, Salesforce.

The 2025 Connectivity Benchmark study also highlighted the importance of automation, with central IT teams governing 70% of automation. A well-rounded automation strategy is considered essential for effectively integrating AI into an organization.

Also: The future of sales? These AI agents offer 24/7 ABC energy for SMBs.

Automation can expand beyond IT delivery teams -- 65% of organizations have developed a complete or nearly complete strategy to empower non-technical people with low-code and no-code solutions. The demand for automation is abundantly clear, with 98% of IT leaders highlighting their need for automation within their organization.

To learn more about the 2025 Connectivity Benchmark research, you can visit here.

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Business leaders are embracing AI, but their employees are not so sure

When incorporated into business operations, AI's ability to act as an assistant in virtually every aspect of a professional's workload should increase efficiency. However, many obstacles, including leadership perceptions of the technology, are preventing widespread adoption by organizations.

To more effective understand how organizations are welcoming AI-related change, Accenture surveyed 3,450 C-suite leaders and 3,000 non-C-suite level employees from organizations worldwide with revenues greater than $500 million.

Also: Microsoft and partners invest $72 million to launch AI Hub in New Jersey.

's research investigation, C-suite leaders anticipate a high level of change in their organizations, with 72% expecting more change in 2025 than in 2024, and 23% expecting the same level. Compared to the expectations for change in 2024, the numbers are slightly lower, with 88% of C-suites in 2024 expecting more change than the year prior.

While a sense of change is palpable, preparedness levels fall short.

Across several industries, fewer C-suite leaders reported feeling "very prepared" to respond to changes in their business environment heading into 2025, compared to how they felt in 2024.

The same sentiment was shared by employees, who felt even less confident. The average level of preparedness for C-suite leaders sat at 43%, while employees' confidence fell to 36%. Despite the joint lack of confidence, leaders are prepared to ramp up AI investments.

A majority (86%) of C-suite leaders feel prepared to up their investment in generative AI in 2025. Similarly, 83% of the leaders claimed their past year's experience with generative AI has allowed them to see "greater potential for positive business impact," in the upcoming year, .

Moreover, a whopping 50% of C-suite leaders see IT as the primary focus of those generative AI investments, followed by engineering, manufacturing, production, and operations (38%), and customer service (29%).

Those areas of focus align with what is generally regarded as the subject areas where generative AI tools can provide meaningful assistance, including STEM-related tasks such as coding, bug fixing, malware detection, math calculations, and threat modeling.

Generative AI also has significant potential to optimize the customer service realm because of its ability to intake robust amounts of data, process it, and then reference it in conversations with people to answer their questions using natural language.

Despite the perceived benefits, obstacles to adoption remain, with C-suite leaders listing a lack of clarity on ROI (26%) and data or technology infrastructure limitations (28%) as limiting factors.

Also: OpenAI tailored ChatGPT Gov for government use - here's what that means.

The disconnect between how leadership and employees perceive the value of implementing generative AI is also a major obstacle; there's a 20% gap between how C-suite leaders and their employees understand "to a great extent" the potential value of generative AI.

Furthermore, employees are less inclined to feel as though their organizations are trained to use the AI tools efficiently, with 55% of employees reporting that comprehensive training and clear guidance would provide them with a boost in confidence using generative AI tools -- signaling a wider need for an increase in effective communication and training.

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AlphaFold 3 predicts the structure and interactions of all of life’s molecules

improvement November 11, 2024: As of November 2024, we have released AlphaFold 3 model code and weights for academic use to help advance research. Learn more about AlphaFold tools.

Original post: Inside every plant, animal and human cell are billions of molecular machines. They’re made up of proteins, DNA and other molecules, but no single piece works on its own. Only by seeing how they interact together, across millions of types of combinations, can we start to truly understand life’s processes.

In a paper , we introduce AlphaFold 3, a revolutionary model that can predict the structure and interactions of all life’s molecules with unprecedented accuracy. For the interactions of proteins with other molecule types we see at least a 50% improvement compared with existing prediction methods, and for some crucial categories of interaction we have doubled prediction accuracy.

We hope AlphaFold 3 will help transform our understanding of the biological world and drug discovery. Scientists can access the majority of its capabilities, for free, through our newly launched AlphaFold Server, an easy-to-use research tool. To build on AlphaFold 3’s potential for drug design, Isomorphic Labs is already collaborating with pharmaceutical companies to apply it to real-world drug design challenges and, ultimately, develop new life-changing treatments for patients.

Our new model builds on the foundations of AlphaFold 2, which in 2020 made a fundamental breakthrough in protein structure prediction. So far, millions of researchers globally have used AlphaFold 2 to make discoveries in areas including malaria vaccines, cancer treatments and enzyme design. AlphaFold has been cited more than 20,000 times and its scientific impact recognized through many prizes, most lately the Breakthrough Prize in Life Sciences. AlphaFold 3 takes us beyond proteins to a broad spectrum of biomolecules. This leap could unlock more transformative science, from developing biorenewable materials and more resilient crops, to accelerating drug design and genomics research.

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