ALEXANDRIA REAL ESTATE EQUITIES INC
For the period ended Sep 30, 2024. Filed Oct 21, 2024.
View on SEC.govAbout this filing
A company's report for each of its first three quarters. The financial statements are not audited. It shows how the business has moved since the last annual report, and what management says changed.
Sep 30, 2024 · Filed Oct 21, 2024
What changed in Risk Factors?
Read the current filingPrevious report: 10-Q
Period ended 2024-06-30; filed 2024-07-22.
0001035443-24-000225
Item 1A. RISK FACTORSCurrent report: 10-Q
Period ended 2024-09-30; filed 2024-10-21.
0001035443-24-000298
Item 1A. RISK FACTORSThe baseline is this issuer’s latest earlier reporting period of the same form that was filed before the current report. A previous 10-Q is a different quarter, not a year-over-year comparison. Amendments are excluded.
Compared 85 previous paragraphs and 37 current paragraphs.
9 unchanged; 5 reworded; 22 added; 71 removed; 0 previous and 1 current paragraphs rearranged.
Tables are not compared: 0 previous and 0 current tables excluded. Dates, whitespace, punctuation and numbering changes are ignored; changes to financial figures remain significant.
A changed paragraph is not evidence that risk increased or decreased. An unchanged paragraph does not establish that risk stayed the same.
The current filing states there were no material changes to risk factors.
This is the filer’s own statement, not a conclusion from the comparison. Read its qualifications and the report it references.
Current filing’s statement
There have been no material changes in our risk factors from those disclosed under the caption “Item 1A. Risk factors” in our
Added paragraphs (22)
Current report
The increased use of artificial intelligence (“AI”) and automation in life science research and development
Current report
(“R&D”) activities may change the uses, space configurations and tenant requirements for our laboratory properties
Current report
In recent years, some life science companies have augmented their traditional laboratory-based R&D efforts by
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integrating AI, cloud computing, quantum computing and other advanced computational technologies into their R&D programs.
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It is expected that such technologies will accelerate and streamline a number of R&D functions, including, for example, through
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the targeted design and evaluation of clinical trials and the efficient identification of the most promising drug development
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candidates from among multiple possible drugs. In addition, life science companies, like companies in many other industries,
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are increasingly integrating new technologies, such as robotics and advanced automation of recurring tasks, into their
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businesses, including their R&D activities. It is widely thought that the life science and healthcare industries, like most
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industries, are in only the early stages of an advanced technology revolution that may have profound, and largely currently
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unknown, impacts on their businesses, including the processes and strategies underlying R&D and commercialization of new
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We have always strived to provide our tenants with state-of-the-art laboratory facilities incorporating cutting-edge
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infrastructure features (including energy delivery, environmental, sustainability, security, and waste disposal features) to enable
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our tenants to perform at the highest levels. It is currently unknown how the ongoing adoption of advanced technologies and
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automation in the life science industry will impact the optimal space configurations and infrastructure features of the “laboratory
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of the future,” and we may face new tenant requirements and requests that will require significant expenditures that may not be
Current report
If technological developments result in a reduction or reconfiguration in space requirements by our tenants, demand by
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individual tenants and prospective tenants for space may decrease over time. If we are not able to offset any reduction in demand from
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the foregoing developments through repurposing space, property dispositions, or other means, the realization of any of the
Removed paragraphs (71)
Previous report
The use of artificial intelligence presents risks and challenges that may adversely impact our business and
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operating results or that of our tenants and vendors or may adversely impact the requirements and demand for life
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We may adopt and integrate generative artificial intelligence and machine learning (collectively, “AI”) tools into our
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operations to enhance efficiencies and streamline existing systems. However, the deployment and maintenance of AI tools
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may entail substantial risks. While these tools hold promise in optimizing processes and driving efficiencies, as with many
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technological innovations, they also pose inherent risks. These include, but are not limited to, the potential for inaccuracy, bias,
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intellectual property infringement, or misappropriation, as well as concerns regarding data privacy and cybersecurity.
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Moreover, the use of AI may introduce errors or inadequacies that are not easily detectable. Deficiencies,
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inaccuracies, or biases in the data used for AI training, or in the content, analyses, or recommendations generated by AI
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applications, may adversely affect our business, financial condition, and results of operations. The legal landscape surrounding
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AI is evolving and remains uncertain. It is unknown how the development of laws in this area could impact our business and
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our ability to enforce our proprietary rights or protect against infringement of those rights.
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Potential risks from the use of AI by our tenants
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The integrationof AI technologies in the life science industry presents both significant opportunities and inherent
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risks. AI predictive models have the potential to enhance the accuracy and usefulness of simulation models and be utilized
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broadly across various stages of drug development. However, the adoption of AI also introduces a complex risk landscape
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similar to those described above that must be navigated with caution.
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Potential risks from the use of AI by our investors, analysts, and other market participants
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The increasing use of AI by investors, analysts, and other market participants for processing, summarizing, and
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interpreting financial and other information, including that in our annual reports on Form 10-K, quarterly reports on Form 10-Q,
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and other public disclosures, poses potential risks. While AI could improve efficiencies in data analysis, AI could also
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inaccurately interpret or summarize information due to algorithmic limitations or misinterpretation of complex financial
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concepts. These misinterpretations could be further exacerbated by the potential for AI to overlook additional disclosures in
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various report sections, such as the Management's Discussion and Analysis of Financial Condition and Results of Operations
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or Risk Factors section within our annual reports on Form 10-K and/or quarterly reports on Form 10-Q.
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Our status as a REIT introduces unique financial metrics, such as funds from operations and fund from operations, as
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adjusted, which represent widely used non-GAAP financial performance measures of equity REITs. Inadequate AI training on
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the aspects unique to our industry could lead to inaccurate interpretations of these financial measures, particularly when
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comparing our performance against non-REIT entities. Furthermore, rules and regulations requiring REITs to distribute at least
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90% of REIT taxable income to stockholders result in a substantial reliance on debt and equity financing by REITs. Without
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adequate training, these unique aspects might not be properly accounted for by AI and could lead to misinterpretations of our
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financial metrics, such as net debt and preferred stock to Adjusted EBITDA, resulting in inaccurate conclusions and misleading
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Additionally, current inconsistencies in the use, calculation, and presentation of non-GAAP measures among public
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companies may lead to AI’s inaccurate interpretations and comparisons of these measures. Without appropriate adjustments
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for these divergences, AI may generate erroneous comparisons with peer companies, distorting the view of our operational
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performance and profitability, which could lead to misguided investor conclusions about our competitive position among other
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Other challenges associated with AI use may include:
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Reworded paragraphs (5)
Previous wording
Moreover, the adoption of AI by our tenants may lead to infrastructure requirements that our buildings currently do not
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entirely recoverable through increased rents. For example, the adoption of AI by our tenants may lead to infrastructure
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accommodate, such as increased power needs due to high-performance computing. Infrastructure upgrades may necessitate
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requirements that our buildings currently do not accommodate, such as increased power needs due to high-performance
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substantial capital expenditures and could potentially impact the environmental footprint of our building operations.
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environmental footprint of our building operations.
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The realization of any of the aforementioned risks could have a material adverse impact on our revenues, net operating
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aforementioned risks could have a material adverse impact on our revenues, net operating income, results of operations, funds from
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income; our results of operations, funds from operations, operating margins, occupancy, EPS, FFO per share; our overall business; and
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operations, operating margins, occupancy, earnings per share, FFO per share, our overall business, and the market value of our
Rearranged current paragraphs (1)
Current report — wording carried from elsewhere
computing. Infrastructure upgrades may necessitate substantial capital expenditures and could potentially impact the