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April 05.2025
3 Minutes Read

AI Investments Are Rising—What You Need to Know About Results and Future Trends

Glowing AI symbol with circuits, representing AI Investments Surge.

Understanding the Surge in AI Investments

The latest survey from Coastal sheds light on an intriguing phenomenon in the business landscape: the simultaneous increase in AI investments amid disappointing outcomes. Despite 67% of companies planning to maintain or increase their spending on AI technologies, only 21% report tangible results. This disparity raises critical questions about the strategies organizations are deploying and their readiness to embrace AI in a meaningful way.

Challenges of AI Implementation

As organizations leap into the AI frontier, they face significant hurdles. The survey shows 43% of respondents identify governance, ethics, and risk as their primary concerns over the next two years. This reflects a growing awareness that simply investing in AI tools is not enough; companies must also establish robust ethical frameworks and governance structures to navigate the complexities of AI deployment.

Roadmap to Success: The Missing Element

One alarming insight from the report is that 64% of companies lack a clear AI roadmap with measurable goals. Eric Berridge, CEO of Coastal, emphasizes that without proper planning and infrastructure, the potential of AI is not only underutilized but also risks misalignment with business goals. A coherent strategy that links AI initiatives to business value is crucial for realizing a strong return on AI investment (ROAI).

Unlocking Real Value from AI

The report outlines several steps organizations can take to enhance their chances of success with AI. Modernizing core infrastructure is vital; companies must ensure their data systems are agile and capable of integrating AI capabilities. Developing unified platforms that can manage data seamlessly across clouds will allow businesses to operate more efficiently with AI.

Agentic Automation and Its Impact on Work

Rethinking operational processes to embrace agentic automation is another path to harnessing the true potential of AI. Companies are increasingly recognizing the importance of not just deploying technology but also transforming workflows that leverage AI’s capabilities. By reimagining how work is performed, organizations can uncover efficiencies that significantly enhance productivity.

Future Trends in AI Investments

The landscape of AI investments is still evolving rapidly. Companies that establish clear data and AI strategies are reportedly 2.7 times more likely to see positive ROI. This statistic serves as a critical reminder for businesses: a proactive approach toward planning for AI is essential in today's competitive landscape. As organizations navigate these transitional waters, aligning investments with proven strategies will yield better outcomes.

Contrasting Views on AI Effectiveness

While the initial results from AI investments may appear disappointing, some experts argue that this may be a temporary phase. As AI technologies mature, the operational efficiencies and competitive advantages they offer could become more pronounced. Businesses that remain committed to their AI initiatives and adapt based on feedback can eventually reap significant rewards. This viewpoint provides a counter-narrative to the pessimism surrounding the current state of AI deployment.

Conclusion: A Call for Action

In light of these findings, organizations must not only increase their AI investments but also focus on developing a structured approach to implementation. Investing in AI should go hand-in-hand with building the right foundation, ensuring that ethical considerations and effective governance are integrated into every step. As the AI ecosystem continues to evolve, staying informed and adaptive will be crucial for businesses aiming to succeed. With the right roadmaps and commitment, companies can transition from merely investing in AI to triumphed outcomes, heralding a new era in business transformation.

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12.09.2025

The Urgent Need for Visibility in Agentic AI Security: Only 21% Have It!

Update Understanding the Rise of Agentic AI in EnterprisesThe Akto 2025 State of Agentic AI Security Report highlights a critical moment in technology adoption: the integration of Agentic AI into mainstream enterprise workflows. This shift signifies not just adoption but a transformative wave reshaping industries like finance, healthcare, and technology. With 31.7% of organizations actively experimenting and 38.6% deploying these AI agents at scale, businesses are racing ahead, but at what cost?The Visibility Gap: A Cause for ConcernOne of the most alarming findings from the report is that only 21% of security leaders have full visibility into the actions of AI agents or their data access behaviors. This alarming statistic underscores the absence of essential oversight mechanisms, allowing potential threats to proliferate unchecked. Security teams are thus faced with a paradox: the faster AI technology is embedded into workflows, the greater the risk of vulnerabilities remaining undetected.Guardrails for the Future: Are We Prepared?The report emphasizes the urgent need for robust guardrails and continuous testing, as a staggering 65% of organizations acknowledge these as critical yet only half have implemented them. Traditional security measures such as manual reviews fall short in environments where AI operates autonomously. This leads security experts to call for a paradigm shift toward proactive strategies that integrate well with the operational pace of AI development.Anticipating the Future: Security Measures Needed by 2026As enterprises gear up for 2026, expectations for Agentic AI security evolve into necessities. Organizations are recognizing the importance of shared security ownership between AppSec and Platform Engineering and standardized permission boundaries across AI access. Continuous agent red teaming, mandatory action-level logging, and thorough risk classification are becoming non-negotiable requirements.The Role of Identity and Access Management in the Age of AIWith the expansion of Agentic AI, identity security must evolve. Companies are faced with the challenge of shadow AI operations—artificial intelligence tools created outside official IT oversight that could harbor risks. As highlighted by industry leaders, the time has come to not just adopt AI, but to do so within a secure framework that integrates identity and access management with a focus on governance.Call to Action: Rethink AI Integration for SecurityThe rapidly changing landscape of Agentic AI calls for more than just awareness; it requires immediate action. As enterprises integrate AI into their operations, they also must commit to proactive security measures that address existing gaps. Ensuring visibility and control over AI agents is not merely advantageous but essential for safeguarding sensitive data and maintaining trust in automated systems.

12.10.2025

Tiny Brain Implant Sends Light Messages To Restore Sensory Perception

Update Unlocking Communication: How a Tiny Implant Transforms Brain Interaction In a groundbreaking study, scientists at Northwestern University have developed a tiny, wireless brain implant that transmits light-based signals directly to the brain, revolutionizing how we understand sensory processing. This remarkable device, smaller than a postage stamp, sits unobtrusively beneath the scalp, where it emits precisely controlled light patterns through the skull to stimulate neurons in the cortex, effectively bypassing traditional sensory pathways. The Science Behind the Light This novel implant utilizes an array of up to 64 micro-LEDs (light-emitting diodes) to generate complex neural patterns that mimic natural sensory activity. In a controlled environment, researchers trained genetically modified mice to recognize specific light patterns associated with rewards, showcasing the implant's potential to communicate essential sensory information directly to the brain. 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As research develops, public perception will likely evolve, paving the way for wider adoption of such technologies. Conclusion: A Call to Embrace the Future The development of this new brain implant marks a monumental step in neuroscience, offering potential solutions to sensory loss and providing valuable insights into the complexities of human perception. As we stand at the intersection of technology and biology, collaboration among scientists, ethicists, and technologists will be essential to harness these innovations responsibly. Let’s embrace this future and be proactive in discussions surrounding brain-computer interfaces and their role in enhancing human capability.

12.08.2025

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Update AI Deployment on the Rise Despite Data Quality Challenges Across the globe, enterprises are increasingly adopting artificial intelligence (AI), with a recent survey finding that 64.5% of organizations now have AI in production. However, the same survey by Apryse reveals a glaring issue: only 38.1% of these enterprises rate their document data as 'excellent' for AI use. This presents a critical gap in AI readiness that is alarming for business leaders keen to harness the disruptive potential of AI technologies. The Paradox of Progress: AI Adoption vs. Data Quality The findings suggest that while AI has cemented its position in the operational landscape of businesses, the infrastructure supporting it—particularly in terms of document data quality—has not kept pace. Traditional data trapped within documents is often messy and inconsistent, posing a significant barrier to effective AI implementation. As Andrew Varley, CPO of Apryse, points out, “AI is no longer experimental, it’s operational,” but many organizations find the document data governance inadequate for leveraging this operational AI effectively. The Financial Impact of Poor Data Quality Many enterprises are now facing significant challenges with data quality, as revealed by a complementary survey from Qlik. It shows that 81% of AI professionals report persistent data quality issues, which could jeopardize the ROI of their AI investments. Poor quality data can lead to biased models and unreliable insights, ultimately compromising the stability of businesses. Financially, organizations need to place increased focus on data quality or risk significant waste and liability. The Role of Document Automation in AI Success The Apryse survey highlights a vital trend: 82.8% of organizations plan to invest in document automation in the next twelve months. Document automation not only streamlines processes but also enhances data quality for AI readiness. Tools that enable the extraction of structured data from unstructured documents—such as improved table recognition and metadata tagging—will be crucial in bridging the gap. By investing in these tools, organizations can unlock the full potential of their AI deployments. Asia-Pacific: A Different Story in AI Maturity While North America remains at the forefront of AI deployment, organizations in Australia and New Zealand are showcasing a surprising leadership in AI infrastructure maturity. These regions are early adopters of data residency rules and have shown a commitment to robust document processing, making them models for other markets. The unique regulatory environment in Oceania—especially in healthcare and financial services—has pushed for solid document-to-data workflows, which may serve as a case study for global enterprises. Key Strategies for Improving Data Quality To overcome the data quality challenges, enterprises must develop comprehensive data management strategies. This includes investing in data governance frameworks, ensuring that all stakeholders understand their roles in maintaining data quality, and implementing continuous data validation processes. Furthermore, utilizing smart automation technologies can help to clean and improve data quality, ensuring reliable foundations for AI models. By adopting these practices, organizations can mitigate risks associated with flawed data and enhance the performance of their AI initiatives. Why Action on Data Quality Matters Now Companies increasingly recognize the urgency of addressing data quality concerns. A fifth of data professionals believe that without prioritizing data quality, businesses face a crisis that could severely outweigh current investments in AI technology. Organizations must act now not just to safeguard investments but to ensure that AI delivers on its promise of operational efficiency and enhanced customer experiences. As industry leaders explore innovative solutions through AI, a commitment to high-quality data is essential for sustainable success. In summary, while the surge in AI adoption is promising, it is accompanied by serious challenges related to data quality and governance. Firms that proactively invest in document automation and enhance data quality practices will stand to gain significant competitive advantages in the evolving AI landscape.

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