Artificial Intelligence
Paylocity Announces Third Quarter Fiscal Year 2023 Financial Results
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- Q3 2023 Recurring & Other Revenue of $314.2 million, up 28% year-over-year
- Q3 2023 Total Revenue of $339.9 million, up 38% year-over-year
SCHAUMBURG, Ill., May 04, 2023 (GLOBE NEWSWIRE) — Paylocity Holding Corporation (Nasdaq: PCTY), a leading provider of cloud-based HCM and payroll software solutions, today announced financial results for the third quarter of fiscal year 2023, which ended March 31, 2023.
“Our overall momentum continued in the third quarter, with Q3 recurring & other revenue growth of 28% and total revenue growth of 38%, as our differentiated value proposition of providing the most modern software in the industry continues to resonate in the marketplace. We continued to build upon our unique value proposition with the recent release of AI Assist, the HCM industry’s first integration of generative AI. Leveraging an integration with Open AI – the developer of ChatGPT – AI Assist is designed to help our clients more easily and effectively communicate and engage with their employees. Additionally, our commitment to product development continues to be recognized, with Paylocity recently placing #1 overall in G2’s Best HR Products list and ranking inside of G2’s Top 25 Global Software companies. Similarly, the strong culture at Paylocity was recognized externally as we received Forbes’s 2023 Best Employers for Diversity award for the second consecutive year,” said Steve Beauchamp, Co-Chief Executive Officer of Paylocity.
Third Quarter Fiscal 2023 Financial Highlights
Revenue:
- Total revenue was $339.9 million, an increase of 38% from the third quarter of fiscal year 2022.
- Recurring & other revenue was $314.2 million, an increase of 28% from the third quarter of fiscal year 2022.
Operating Income:
- GAAP operating income was $80.4 million and Non-GAAP operating income was $116.7 million in the third quarter of fiscal year 2023.
Net Income:
- GAAP net income was $57.6 million or $1.02 per share in the third quarter of fiscal year 2023 based on 56.6 million diluted weighted average common shares outstanding.
Adjusted EBITDA:
- Adjusted EBITDA, a non-GAAP measure, was $130.7 million in the third quarter of fiscal year 2023.
Balance Sheet and Cash Flow:
- Cash and cash equivalents totaled $233.7 million as of the third quarter of fiscal year 2023.
- Cash flow from operations for the first nine months of fiscal year 2023 was $206.1 million.
- As of March 31, 2023, Paylocity had no long-term debt and had not drawn on its credit facility.
A reconciliation of GAAP to non-GAAP financial measures has been provided in this press release, including the accompanying tables. An explanation of these measures is also included below under the heading “Non-GAAP Financial Measures.”
Business Outlook
Based on information available as of May 4, 2023, Paylocity is issuing guidance for the fourth quarter and full fiscal year 2023 as indicated below.
Fourth Quarter 2023:
- Total revenue is expected to be in the range of $299.2 million to $303.2 million, which represents approximately 32% growth over fiscal year 2022 fourth quarter total revenue.
- Adjusted EBITDA, a non-GAAP measure, is expected to be in the range of $93.5 million to $96.5 million.
Fiscal Year 2023:
- Total revenue is expected to be in the range of $1.165 billion to $1.169 billion, which represents approximately 37% growth over fiscal year 2022 total revenue.
- Adjusted EBITDA, a non-GAAP measure, is expected to be in the range of $368.1 million to $371.1 million.
We are unable to reconcile forward-looking non-GAAP Adjusted EBITDA to its directly comparable GAAP financial measure because the information which is needed to complete a reconciliation is unavailable at this time without unreasonable effort.
Conference Call Details
Paylocity will host a conference call to discuss its third quarter fiscal year 2023 results at 4:30 p.m. Central Time today (5:30 p.m. Eastern Time). A live audio webcast of the conference call along with detailed financial information can be accessed through https://investors.paylocity.com/events-and-presentations where dial in details are provided. A replay of the call will be available and archived via webcast at https://investors.paylocity.com/.
About Paylocity
Paylocity is a leading provider of cloud-based HCM and payroll software solutions headquartered in Schaumburg, IL. Founded in 1997 and publicly traded since 2014, Paylocity offers an intuitive, easy-to-use product suite that helps businesses tackle today’s challenges while moving them toward the promise of tomorrow. Known for its unique culture and consistently recognized as one of the best places to work, Paylocity accompanies its clients on the journey to create great workplaces and help people achieve their best through automation, data-driven insights, and engagement. For more information, visit www.paylocity.com.
Non-GAAP Financial Measures
The company uses certain non-GAAP financial measures in this release, including Adjusted EBITDA, Adjusted EBITDA margin, adjusted gross profit, adjusted gross profit margin, non-GAAP operating income, non-GAAP net income, non-GAAP net income per share, non-GAAP sales and marketing, non-GAAP total research and development and non-GAAP general and administrative, free cash flow and free cash flow margin. Generally, a non-GAAP financial measure is a numerical measure of a company’s performance, financial position or cash flow that either excludes or includes amounts that are not normally excluded or included in the most directly comparable measure calculated and presented in accordance with GAAP. We define Adjusted EBITDA as net income (loss) before interest expense, income tax expense (benefit), and depreciation and amortization expense, adjusted to eliminate stock-based compensation expense and employer payroll taxes related to stock releases and option exercises and other items as described later in this release. We calculate Adjusted EBITDA margin as adjusted EBITDA as described in the preceding sentence divided by total revenues. Adjusted gross profit is adjusted to eliminate stock-based compensation expense and employer payroll taxes related to stock releases and option exercises and amortization of capitalized internal-use software costs and certain acquired intangibles. Adjusted gross profit margin is calculated as adjusted gross profit as described in the preceding sentence divided by total revenues. Non-GAAP operating income is adjusted to eliminate stock-based compensation expense and employer payroll taxes related to stock releases and option exercises, the amortization of acquired intangibles and other items as described later in this release. Non-GAAP sales and marketing expense is adjusted to eliminate stock-based compensation expense and employer payroll taxes related to stock releases and option exercises and other items as described later in this release. Non-GAAP general and administrative expense is adjusted to eliminate stock-based compensation expense and employer payroll taxes related to stock releases and option exercises, the amortization of certain acquired intangibles and other items as described later in this release. Non-GAAP net income and non-GAAP net income per share are adjusted to eliminate stock-based compensation expense and employer payroll taxes related to stock releases and option exercises, the amortization of acquired intangibles and other items as described later in this release, including the income tax effect on these items. Non-GAAP total research and development is adjusted for capitalized internal-use software costs paid and to eliminate stock-based compensation expense and employer payroll taxes related to stock releases and option exercises and other items as described later in this release. Free cash flow is defined as net cash provided by operating activities less capitalized internal-use software costs, purchase of property and equipment and lease allowances used for tenant improvements. Free cash flow margin is calculated by dividing free cash flow as defined in the preceding sentence divided by total revenues. Please note that other companies may define their non-GAAP financial measures differently than we do. Management presents certain non-GAAP financial measures in this release because it considers them to be important supplemental measures of performance. Management uses these non-GAAP financial measures for planning purposes, including analysis of the company’s performance against prior periods, the preparation of operating budgets and to determine appropriate levels of operating and capital investments. Management believes that these non-GAAP financial measures provide additional insight for analysts and investors in evaluating the company’s financial and operational performance. Management also intends to provide these non-GAAP financial measures as part of the company’s future earnings discussions and, therefore, the inclusion of the non-GAAP financial measures should provide consistency in the company’s financial reporting. Non-GAAP financial measures have limitations as an analytical tool. Investors are encouraged to review the reconciliation of the non-GAAP measures to their most directly comparable GAAP measures provided in this release.
Safe Harbor/Forward Looking Statements
This press release contains forward-looking statements that involve substantial risks and uncertainties. All statements, other than statements of historical facts, included herein regarding Paylocity’s future operations, ability to scale its business, future financial position and performance, future revenues, projected costs, prospects, plans and objectives of management are forward-looking statements. The words “anticipate,” “believe,” “estimate,” “expect,” “intend,” “may,” “plan,” “will,” “would,” “seek” and similar expressions (or the negative of these terms) are intended to identify forward-looking statements, although not all forward-looking statements contain these identifying words. These forward-looking statements include, among other things, statements about management’s estimates regarding future revenues and financial performance and other statements about management’s beliefs, intentions or goals. Paylocity may not actually achieve the expectations disclosed in the forward-looking statements, and you should not place undue reliance on Paylocity’s forward-looking statements. These forward-looking statements involve risks and uncertainties that could cause actual results or events to differ materially from the expectations disclosed in the forward-looking statements, including, but not limited to the general economic conditions in regions in which Paylocity does business, including the ongoing impact of the novel coronavirus disease (“COVID-19”) on the U.S. and the global economy, changes in interest rates, business disruptions, reductions in employment and an increase in business failures that have occurred or may occur in the future; the continuing impact of COVID-19 on Paylocity’s employees and clients; Paylocity’s ability to leverage AI Assist and other forms of artificial intelligence and machine learning in its technology, which may be constrained by current and future laws, regulations, interpretive positions or standards governing new and evolving technologies and ethical considerations that could restrict or impose burdensome and costly requirements on its ability to continue to leverage data in innovative ways; Paylocity’s ability to retain existing clients and to attract new clients to enter into subscriptions for its services; the challenges associated with a growing company’s ability to effectively service clients in a dynamic and competitive market; challenges associated with expanding and evolving a sales organization to effectively address new geographies and products and services; challenges related to cybersecurity threats and evolving cybersecurity regulations; Paylocity’s reliance on and ability to expand its referral network of third parties; Paylocity’s reliance on third party payroll partners in foreign jurisdictions in its Blue Marble business; difficulties associated with accurately forecasting revenue and appropriately planning expenses; challenges with managing growth effectively; risks related to regulatory, legislative and judicial uncertainty in Paylocity’s markets; Paylocity’s ability to protect and defend its intellectual property; the risk that Paylocity’s security measures are compromised or a threat actor gains unauthorized access to customer data; unexpected events in the market for Paylocity’s solutions; changes in the competitive environment in Paylocity’s industry and the markets in which it operates; adverse changes in general economic or market conditions; changes in the employment rates of Paylocity’s clients and the resultant impact on revenue; the possibility that Paylocity may be adversely affected by other economic, business, and/or competitive factors; and other risks and potential factors that could affect Paylocity’s business and financial results identified in Paylocity’s filings with the Securities and Exchange Commission (the “SEC”), including its 10-K filed with the SEC on August 5, 2022. Additional information will also be set forth in Paylocity’s future quarterly reports on Form 10-Q, annual reports on Form 10-K and other filings that Paylocity makes with the SEC. These forward-looking statements represent Paylocity’s expectations as of the date of this press release. Subsequent events may cause these expectations to change, and Paylocity disclaims any obligations to update or alter these forward-looking statements in the future, whether as a result of new information, future events or otherwise.
| PAYLOCITY HOLDING CORPORATION | |||||||
| Unaudited Consolidated Balance Sheets | |||||||
| (in thousands, except per share data) | |||||||
| June 30, | March 31, | ||||||
| 2022 | 2023 | ||||||
| Assets | |||||||
| Current assets: | |||||||
| Cash and cash equivalents | $ | 139,756 | $ | 233,692 | |||
| Accounts receivable, net | 15,754 | 27,449 | |||||
| Deferred contract costs | 59,501 | 73,574 | |||||
| Prepaid expenses and other | 28,896 | 28,880 | |||||
| Total current assets before funds held for clients | 243,907 | 363,595 | |||||
| Funds held for clients | 3,987,776 | 3,202,415 | |||||
| Total current assets | 4,231,683 | 3,566,010 | |||||
| Capitalized internal-use software, net | 61,985 | 78,374 | |||||
| Property and equipment, net | 62,839 | 60,067 | |||||
| Operating lease right-of-use assets | 49,210 | 45,006 | |||||
| Intangible assets, net | 45,475 | 37,164 | |||||
| Goodwill | 101,949 | 102,054 | |||||
| Long-term deferred contract costs | 229,067 | 280,310 | |||||
| Long‑term prepaid expenses and other | 7,746 | 6,842 | |||||
| Deferred income tax assets | 19,060 | 17,690 | |||||
| Total assets | $ | 4,809,014 | $ | 4,193,517 | |||
| Liabilities and Stockholders’ Equity | |||||||
| Current liabilities: | |||||||
| Accounts payable | $ | 8,374 | $ | 7,968 | |||
| Accrued expenses | 124,384 | 144,281 | |||||
| Total current liabilities before client fund obligations | 132,758 | 152,249 | |||||
| Client fund obligations | 3,987,776 | 3,202,415 | |||||
| Total current liabilities | 4,120,534 | 3,354,664 | |||||
| Long-term operating lease liabilities | 69,119 | 64,060 | |||||
| Other long-term liabilities | 3,681 | 3,830 | |||||
| Deferred income tax liabilities | 2,217 | 2,217 | |||||
| Total liabilities | $ | 4,195,551 | $ | 3,424,771 | |||
| Stockholders’ equity: | |||||||
| Preferred stock, $0.001 par value, 5,000 authorized, no shares issued and outstanding at June 30, 2022 and March 31, 2023 | $ | — | $ | — | |||
| Common stock, $0.001 par value, 155,000 shares authorized at June 30, 2022 and March 31, 2023; 55,190 shares issued and outstanding at June 30, 2022 and 55,810 shares issued and outstanding at March 31, 2023 | 55 | 56 | |||||
| Additional paid-in capital | 289,843 | 341,494 | |||||
| Retained earnings | 325,868 | 429,436 | |||||
| Accumulated other comprehensive loss | (2,303 | ) | (2,240 | ) | |||
| Total stockholders’ equity | $ | 613,463 | $ | 768,746 | |||
| Total liabilities and stockholders’ equity | $ | 4,809,014 | $ | 4,193,517 | |||
| PAYLOCITY HOLDING CORPORATION | |||||||||||||
| Unaudited Consolidated Statements of Operations and Comprehensive Income | |||||||||||||
| (in thousands, except per share data) | |||||||||||||
| Three Months Ended | Nine Months Ended | ||||||||||||
| March 31, | March 31, | ||||||||||||
| 2022 | 2023 | 2022 | 2023 | ||||||||||
| Revenues: | |||||||||||||
| Recurring and other revenue | $ | 244,962 | $ | 314,170 | $ | 620,827 | $ | 816,010 | |||||
| Interest income on funds held for clients | 1,008 | 25,687 | 2,877 | 50,135 | |||||||||
| Total revenues | 245,970 | 339,857 | 623,704 | 866,145 | |||||||||
| Cost of revenues | 75,538 | 95,714 | 209,608 | 270,333 | |||||||||
| Gross profit | 170,432 | 244,143 | 414,096 | 595,812 | |||||||||
| Operating expenses: | |||||||||||||
| Sales and marketing | 52,752 | 74,064 | 154,856 | 220,821 | |||||||||
| Research and development | 25,670 | 42,323 | 74,024 | 123,445 | |||||||||
| General and administrative | 44,632 | 47,379 | 119,448 | 145,872 | |||||||||
| Total operating expenses | 123,054 | 163,766 | 348,328 | 490,138 | |||||||||
| Operating income | 47,378 | 80,377 | 65,768 | 105,674 | |||||||||
| Other income (expense) | (311 | ) | 1,139 | (800 | ) | 971 | |||||||
| Income before income taxes | 47,067 | 81,516 | 64,968 | 106,645 | |||||||||
| Income tax expense (benefit) | 12,221 | 23,900 | (10,663 | ) | 3,077 | ||||||||
| Net income | $ | 34,846 | $ | 57,616 | $ | 75,631 | $ | 103,568 | |||||
| Other comprehensive income (loss), net of tax | (1,218 | ) | 1,919 | (1,628 | ) | 63 | |||||||
| Comprehensive income | $ | 33,628 | $ | 59,535 | $ | 74,003 | $ | 103,631 | |||||
| Net income per share: | |||||||||||||
| Basic | $ | 0.63 | $ | 1.03 | $ | 1.38 | $ | 1.86 | |||||
| Diluted | $ | 0.62 | $ | 1.02 | $ | 1.34 | $ | 1.83 | |||||
| Weighted-average shares used in computing net income per share: | |||||||||||||
| Basic | 55,114 | 55,788 | 54,996 | 55,653 | |||||||||
| Diluted | 56,367 | 56,555 | 56,437 | 56,560 | |||||||||
Stock-based compensation expense and employer payroll taxes related to stock releases and option exercises for each of the three and nine months ended March 31, are included in the above line items:
| Three Months Ended | Nine Months Ended | ||||||||||||
| March 31, | March 31, | ||||||||||||
| 2022 | 2023 | 2022 | 2023 | ||||||||||
| Cost of revenues | $ | 2,978 | $ | 4,341 | $ | 9,832 | $ | 14,696 | |||||
| Sales and marketing | 5,213 | 9,038 | 16,982 | 30,409 | |||||||||
| Research and development | 4,911 | 8,993 | 15,131 | 30,699 | |||||||||
| General and administrative | 11,538 | 11,161 | 32,921 | 46,688 | |||||||||
| Total stock-based compensation expense and employer payroll taxes related to stock releases and option exercises | $ | 24,640 | $ | 33,533 | $ | 74,866 | $ | 122,492 | |||||
| PAYLOCITY HOLDING CORPORATION | |||||||
| Unaudited Consolidated Statements of Cash Flows | |||||||
| (in thousands) | |||||||
| Nine Months Ended | |||||||
| March 31, | |||||||
| 2022 | 2023 | ||||||
| Cash flows from operating activities: | |||||||
| Net income | $ | 75,631 | $ | 103,568 | |||
| Adjustments to reconcile net income to net cash provided by operating activities: | |||||||
| Stock-based compensation expense | 70,197 | 116,002 | |||||
| Depreciation and amortization expense | 36,419 | 44,481 | |||||
| Deferred income tax expense (benefit) | (10,882 | ) | 1,308 | ||||
| Provision for credit losses | 238 | 864 | |||||
| Net amortization of premiums (accretion of discounts) on available-for-sale securities | 342 | (3,602 | ) | ||||
| Amortization of debt issuance costs | 136 | 221 | |||||
| Other | 286 | 1,346 | |||||
| Changes in operating assets and liabilities: | |||||||
| Accounts receivable | (9,654 | ) | (12,548 | ) | |||
| Deferred contract costs | (49,205 | ) | (62,929 | ) | |||
| Prepaid expenses and other | (9,418 | ) | 2,031 | ||||
| Accounts payable | 141 | 10 | |||||
| Accrued expenses and other | 1,163 | 15,355 | |||||
| Net cash provided by operating activities | 105,394 | 206,107 | |||||
| Cash flows from investing activities: | |||||||
| Purchases of available-for-sale securities | (215,538 | ) | (557,403 | ) | |||
| Proceeds from sales and maturities of available-for-sale securities | 85,875 | 298,113 | |||||
| Capitalized internal-use software costs | (26,285 | ) | (30,726 | ) | |||
| Purchases of property and equipment | (15,355 | ) | (8,769 | ) | |||
| Acquisitions of businesses, net of cash acquired | (107,576 | ) | — | ||||
| Other investing activities | (2,500 | ) | 33 | ||||
| Net cash used in investing activities | (281,379 | ) | (298,752 | ) | |||
| Cash flows from financing activities: | |||||||
| Net change in client fund obligations | 2,564,829 | (785,361 | ) | ||||
| Borrowings under credit facility | 50,000 | — | |||||
| Repayment of credit facility | (50,000 | ) | — | ||||
| Proceeds from employee stock purchase plan | 7,216 | 8,450 | |||||
| Taxes paid related to net share settlement of equity awards | (68,509 | ) | (84,174 | ) | |||
| Payment of debt issuance costs | (64 | ) | (873 | ) | |||
| Net cash provided by (used in) financing activities | 2,503,472 | (861,958 | ) | ||||
| Net change in cash, cash equivalents and funds held for clients’ cash and cash equivalents | 2,327,487 | (954,603 | ) | ||||
| Cash, cash equivalents and funds held for clients’ cash and cash equivalents—beginning of period | 1,945,881 | 3,793,453 | |||||
| Cash, cash equivalents and funds held for clients’ cash and cash equivalents—end of period | $ | 4,273,368 | $ | 2,838,850 | |||
| Supplemental Disclosure of Non-Cash Investing and Financing Activities | |||||||
| Purchases of property and equipment and internal-use software, accrued but not paid | $ | 1,251 | $ | 3,115 | |||
| Liabilities assumed for acquisitions | $ | 4,470 | $ | 117 | |||
| Supplemental Disclosure of Cash Flow Information | |||||||
| Cash paid for interest | $ | 257 | $ | 282 | |||
| Cash paid (refunds received) for income taxes | $ | (115 | ) | $ | 573 | ||
| Reconciliation of cash, cash equivalents and funds held for clients’ cash and cash equivalents to the Consolidated Balance Sheets | |||||||
| Cash and cash equivalents | $ | 96,465 | $ | 233,692 | |||
| Funds held for clients’ cash and cash equivalents | 4,176,903 | 2,605,158 | |||||
| Total cash, cash equivalents and funds held for clients’ cash and cash equivalents | $ | 4,273,368 | $ | 2,838,850 | |||
| Paylocity Holding Corporation | |||||||||||||||
| Reconciliation of GAAP to non-GAAP Financial Measures | |||||||||||||||
| (In thousands except per share data) | |||||||||||||||
| Three Months Ended | Nine Months Ended | ||||||||||||||
| March 31, | March 31, | ||||||||||||||
| 2022 | 2023 | 2022 | 2023 | ||||||||||||
| Reconciliation from Gross profit to Adjusted gross profit: | |||||||||||||||
| Gross profit | $ | 170,432 | $ | 244,143 | $ | 414,096 | $ | 595,812 | |||||||
| Amortization of capitalized internal-use software costs | 6,308 | 7,984 | 18,523 | 22,504 | |||||||||||
| Amortization of certain acquired intangibles | — | 1,854 | — | 5,561 | |||||||||||
| Stock-based compensation expense and employer payroll taxes related to stock releases and option exercises | 2,978 | 4,341 | 9,832 | 14,696 | |||||||||||
| Other items (1) | 46 | — | 94 | 19 | |||||||||||
| Adjusted gross profit | $ | 179,764 | $ | 258,322 | $ | 442,545 | $ | 638,592 | |||||||
| Three Months Ended | Nine Months Ended | ||||||||||||||
| March 31, | March 31, | ||||||||||||||
| 2022 | 2023 | 2022 | 2023 | ||||||||||||
| Reconciliation from Operating income to Non-GAAP Operating income: | |||||||||||||||
| Operating income | $ | 47,378 | $ | 80,377 | $ | 65,768 | $ | 105,674 | |||||||
| Stock-based compensation expense and employer payroll taxes related to stock releases and option exercises | 24,640 | 33,533 | 74,866 | 122,492 | |||||||||||
| Amortization of acquired intangibles | 2,630 | 2,770 | 5,982 | 8,311 | |||||||||||
| Other items (2) | 806 | 30 | 1,609 | 446 | |||||||||||
| Non-GAAP Operating income | $ | 75,454 | $ | 116,710 | $ | 148,225 | $ | 236,923 | |||||||
| Three Months Ended | Nine Months Ended | ||||||||||||||
| March 31, | March 31, | ||||||||||||||
| 2022 | 2023 | 2022 | 2023 | ||||||||||||
| Reconciliation from Net income to Non-GAAP Net income: | |||||||||||||||
| Net income | $ | 34,846 | $ | 57,616 | $ | 75,631 | $ | 103,568 | |||||||
| Stock-based compensation expense and employer payroll taxes related to stock releases and option exercises | 24,640 | 33,533 | 74,866 | 122,492 | |||||||||||
| Amortization of acquired intangibles | 2,630 | 2,770 | 5,982 | 8,311 | |||||||||||
| Other items (2) | 806 | 30 | 1,817 | 446 | |||||||||||
| Income tax effect on adjustments (3) | 5,869 | 4,540 | (20,060 | ) | (17,899 | ) | |||||||||
| Non-GAAP Net income | $ | 68,791 | $ | 98,489 | $ | 138,236 | $ | 216,918 | |||||||
| Three Months Ended | Nine Months Ended | ||||||||||||||
| March 31, | March 31, | ||||||||||||||
| 2022 | 2023 | 2022 | 2023 | ||||||||||||
| Calculation of Non-GAAP Net income per share: | |||||||||||||||
| Non-GAAP Net income | $ | 68,791 | $ | 98,489 | $ | 138,236 | $ | 216,918 | |||||||
| Diluted weighted-average number of common shares | 56,367 | 56,555 | 56,437 | 56,560 | |||||||||||
| Non-GAAP Net income per share | $ | 1.22 | $ | 1.74 | $ | 2.45 | $ | 3.84 | |||||||
| Three Months Ended | Nine Months Ended | ||||||||||||||
| March 31, | March 31, | ||||||||||||||
| 2022 | 2023 | 2022 | 2023 | ||||||||||||
| Reconciliation from Net income to Adjusted EBITDA: | |||||||||||||||
| Net income | $ | 34,846 | $ | 57,616 | $ | 75,631 | $ | 103,568 | |||||||
| Interest expense | 168 | 187 | 386 | 564 | |||||||||||
| Income tax expense (benefit) | 12,221 | 23,900 | (10,663 | ) | 3,077 | ||||||||||
| Depreciation and amortization expense | 13,036 | 15,387 | 36,419 | 44,481 | |||||||||||
| EBITDA | 60,271 | 97,090 | 101,773 | 151,690 | |||||||||||
| Stock-based compensation expense and employer payroll taxes related to stock releases and option exercises | 24,640 | 33,533 | 74,866 | 122,492 | |||||||||||
| Other items (2) | 806 | 30 | 1,817 | 446 | |||||||||||
| Adjusted EBITDA | $ | 85,717 | $ | 130,653 | $ | 178,456 | $ | 274,628 | |||||||
| Three Months Ended | Nine Months Ended | ||||||||||||||
| March 31, | March 31, | ||||||||||||||
| 2022 | 2023 | 2022 | 2023 | ||||||||||||
| Reconciliation of Non-GAAP sales and marketing: | |||||||||||||||
| Sales and marketing | $ | 52,752 | $ | 74,064 | $ | 154,856 | $ | 220,821 | |||||||
| Stock-based compensation expense and employer payroll taxes related to stock releases and option exercises | 5,213 | 9,038 | 16,982 | 30,409 | |||||||||||
| Other items (1) | 60 | — | 162 | 22 | |||||||||||
| Non-GAAP sales and marketing | $ | 47,479 | $ | 65,026 | $ | 137,712 | $ | 190,390 | |||||||
| Three Months Ended | Nine Months Ended | ||||||||||||||
| March 31, | March 31, | ||||||||||||||
| 2022 | 2023 | 2022 | 2023 | ||||||||||||
| Reconciliation of Non-GAAP total research and development: | |||||||||||||||
| Research and development | $ | 25,670 | $ | 42,323 | $ | 74,024 | $ | 123,445 | |||||||
| Capitalized internal-use software costs | 8,319 | 10,986 | 26,285 | 30,726 | |||||||||||
| Stock-based compensation expense and employer payroll taxes related to stock releases and option exercises | 4,911 | 8,993 | 15,131 | 30,699 | |||||||||||
| Other items (1) | 218 | 30 | 686 | 399 | |||||||||||
| Non-GAAP total research and development | $ | 28,860 | $ | 44,286 | $ | 84,492 | $ | 123,073 | |||||||
| Three Months Ended | Nine Months Ended | ||||||||||||||
| March 31, | March 31, | ||||||||||||||
| 2022 | 2023 | 2022 | 2023 | ||||||||||||
| Reconciliation of Non-GAAP general and administrative: | |||||||||||||||
| General and administrative | $ | 44,632 | $ | 47,379 | $ | 119,448 | $ | 145,872 | |||||||
| Stock-based compensation expense and employer payroll taxes related to stock releases and option exercises | 11,538 | 11,161 | 32,921 | 46,688 | |||||||||||
| Amortization of certain acquired intangibles | 2,630 | 916 | 5,982 | 2,750 | |||||||||||
| Other items (2) | 482 | — | 667 | 6 | |||||||||||
| Non-GAAP general and administrative | $ | 29,982 | $ | 35,302 | $ | 79,878 | $ | 96,428 | |||||||
| Nine Months Ended | ||||||||
| March 31, | ||||||||
| 2022 | 2023 | |||||||
| Reconciliation of Free Cash Flow: | ||||||||
| Net cash provided by operating activities | $ | 105,394 | $ | 206,107 | ||||
| Capitalized internal-use software costs | (26,285 | ) | (30,726 | ) | ||||
| Purchases of property and equipment | (15,355 | ) | (8,769 | ) | ||||
| Free Cash Flow | $ | 63,754 | $ | 166,612 | ||||
(1) Represents certain nonrecurring acquisition-related costs.
(2) Represents nonrecurring costs including acquisition and other transaction-related costs and lease exit activity.
(3) Includes the income tax effect on non-GAAP net income adjustments related to stock-based compensation expense and employer payroll taxes related to stock releases and option exercises, amortization of acquired intangibles and other items, which include acquisition and other transaction-related costs and lease exit activity.
Artificial Intelligence
Data Center Chip Market Size was Valued at USD 11.7 Billion in 2022 and is Expected to Reach USD 45.3 Billion by 2032 at a CAGR of 14.6% | Valuates Reports
BANGALORE, India, July 26, 2024 /PRNewswire/ — Data Center Chip Market By Chip Type (GPU, ASIC, FPGA, CPU, Others), By Data Center Size (Small and Medium Size, Large Size), By Industry Verticals (BFSI, Manufacturing, Government, IT and Telecom, Retail, Transportation, Energy and Utilities, Others): Global Opportunity Analysis and Industry Forecast, 2023-2032.
The Data Center Chip Market was valued at USD 11.7 Billion in 2022, and is estimated to reach USD 45.3 Billion by 2032, growing at a CAGR of 14.6% from 2023 to 2032.
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Major Factors Driving the Growth of Data Center Chip Market
Because of the growing need for data processing and storage solutions brought about by the quick development of cloud computing, artificial intelligence, and big data analytics, the data center chip market is expanding significantly. High-performance chips are necessary for data centers to process massive volumes of data quickly and efficiently. As a result, advances in chip technology, including CPUs, GPUs, and specialist AI processors, have been made. The need for more resilient and scalable data center infrastructure is fueled in part by the expansion of digital services and Internet of Things (IoT) devices. The market is expanding due to key areas including Asia-Pacific, with its investments in technology and fast digital transformation, and North America, with its top tech businesses and vast data center networks.
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TRENDS INFLUENCING THE GROWTH OF THE DATA CENTER CHIP MARKET:
In data centers, Graphics Processing Units (GPUs) are essential for speeding up computing operations and data processing. They are perfect for managing workloads related to artificial intelligence (AI), machine learning, and large-scale data analytics because of their parallel processing capabilities. The need for GPUs in data centers is growing as these technologies become increasingly essential to corporate operations. Businesses are purchasing GPUs in order to increase the effectiveness of their data processing, lower latency, and boost overall performance. The need for data center chips is being driven by the increasing reliance on GPUs for sophisticated computing activities, which is considerably contributing to the market’s rise. This need is further increased by the growing use of AI and machine learning in a variety of sectors, which puts GPUs at the forefront of the data center semiconductor industry.
Compared to general-purpose chips, Application Specific Integrated Circuits (ASICs) provide better performance and efficiency since they are designed specifically for a given application. ASICs are extensively utilized in data centers for specific tasks including networking, data compression, and encryption. ASICs are becoming more and more common as a result of the growth of cloud computing, big data analytics, and blockchain technology, which has increased demand for high-performance, energy-efficient processors. Their capacity to provide tailored performance for certain applications aids data centers in better workload management, power conservation, and operating expense reduction. The market is expanding as a result of the increased preference for ASICs in data centers, which is fueling the need for specialized data center chips.
Large data centers are important users of data center chips; they are run by well-known IT firms and cloud service providers. To manage enormous volumes of data and provide a wide range of services, these facilities need a great deal of processing power and sophisticated computing skills. High-performance data center chips are becoming more and more necessary as a result of the growth of massive data centers and the rising demand for online streaming, cloud services, and digital transactions. These chips are necessary to ensure effective data management, processing, and storage, which helps big data centers fulfill the increasing expectations of its clientele. Large data center proliferation is anticipated to considerably boost the data center chip industry as the digital economy continues to grow.
Data centers are becoming more and more important to the Banking, Financial Services, and Insurance (BFSI) industry as a means of safely and effectively managing high transaction volumes, consumer data, and financial records. The need for sophisticated data center processors is being driven by the sector’s requirement for real-time data processing, high-performance computing, and strong security measures. BFSI organizations may improve their operational efficiency, guarantee data integrity, and deliver superior client services by utilizing data centers fitted with robust chips. The BFSI sector’s need for data center chips is being driven by the increasing use of online banking, digital banking, and financial analytics tools, all of which increase the requirement for sophisticated data center infrastructure.
The market for data center chips is significantly influenced by the cloud computing industry’s explosive growth. There is a growing need for scalable, effective, and high-performance data center infrastructure as more companies move their operations to the cloud. In order to handle enormous volumes of data, facilitate virtualization, and guarantee flawless service delivery, cloud service providers need sophisticated data center chips. Sturdy data center chips are becoming more and more necessary as cloud-based solutions become more and more popular. Benefits like cost savings, flexibility, and scalability are driving this trend. In places like North America and Europe, where cloud adoption rates are high and data center chip demand is rising rapidly, this tendency is especially significant.
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DATA CENTER CHIP MARKET SHARE
In 2022, North America gained a sizable portion of the market.
In 2022, the GPU made up the largest portion of the market share.
Throughout the projection period, large data centers are expected to gain a significant portion.
The BFSI market is anticipated to be one of the most profitable markets.
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Key Companies:
Advanced Micro Devices IncTaiwan Semiconductor Manufacturing Company LimitedBroadcomHuawei Technologies Co LtdIntel CorporationNVidia CorporationSamsung Electronics Co LtdQualcomm Technologies IncGlobalFoundriesARM LIMITED (SOFTBANK GROUP CORP.)Purchase Chapters @ https://reports.valuates.com/request/chaptercost/ALLI-Auto-2B326/Data_Center_Chip_Market
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Artificial Intelligence
Industry 4.0 Market to Surpass USD 513.89 Billion by 2031 with Automation Surge | SkyQuest Technology
WESTFORD, Mass., July 26, 2024 /PRNewswire/ — According to SkyQuest, the global Industry 4.0 Market size was valued at USD 133.05 billion in 2022 and is poised to grow from USD 154.6 billion in 2023 to USD 513.89 billion by 2031, growing at a CAGR of 16.2% during the forecast period (2024-2031).
Industry 4.0 or the fourth industrial revolution emphasizes the use of automation and interconnectivity. Employment of advanced technologies such as artificial intelligence, machine learning, robotics, and connected devices to improve the productivity and efficiency of industries. Rapid digitization and advancements in technology are forecasted to bolster the Industry 4.0 market growth over the coming years. The global Industry 4.0 market is segmented into technology, industry vertical, and region.
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Industry 4.0 Market Overview:
Report Coverage
Details
Market Revenue in 2023
$ 154.6 billion
Estimated Value by 2031
$ 513.89 billion
Growth Rate
Poised to grow at a CAGR of 16.2%
Forecast Period
2024–2031
Forecast Units
Value (USD Billion)
Report Coverage
Revenue Forecast, Competitive Landscape, Growth Factors, and Trends
Segments Covered
Technology, Industry and Region
Geographies Covered
North America, Europe, Asia Pacific, Latin America, and Middle East and Africa.
Report Highlights
Internet of Things (IoT) technology takes centerstage for Industry 4.0 adoption
Key Market Opportunities
Adoption of smart manufacturing and additive manufacturing practices
Key Market Drivers
Rising demand for automation across all industry verticals
Segments covered in Industry 4.0 Market are as follows:
TechnologyRobots (Traditional Industrial Robots {Articulated robots, Cartesian Robots, Selective Compliance Assembly Robot Arm (SCARA), Cylindrical Robots, Others}, Collaborative Robots), Blockchain in Manufacturing, Industrial Sensors (Level Sensors, Temperature Sensors, Flow Sensors, Position Sensors, Pressure Sensors, Force Sensors, Humidity & Moisture Sensors, Gas Sensors), Industrial 3D Printing, Machine Vision (Camera {Digital Camera, Smart Camera}, Frame Grabbers, Optics, and LED Lighting, Processor and Software), HMI (Offering {Hardware [Basic HMI, Advanced Panel-based HMI, Advanced PC-based HMI, Others], Software [On-premises HMI, Cloud-based HMI], Services}), Configuration ({Embedded HMI, Standalone HMI}, Technology {Motion HMI, Bionic HMI, Tactile HMI, Acoustic HMI}, End-user Industry {Process industries [Oil & Gas, Food & beverages, Pharmaceuticals, Chemicals, Energy & power, Metals & mining, Water & wastewater, Others], Discrete industry [Automotive, Aerospace & defense, Packaging, Medical devices, Semiconductor & electronics, Others]}), AI In Manufacturing (Offering {Hardware [Processor MPU, GPU, FPGA, ASIC, Memory, Network], Software [AI solutions- | On-premises, Cloud |, AI platform- | Machine learning framework, Application program interface |], Services [Deployment & integration, Support & maintenance]}, Technology {Machine learning [Deep learning, Supervised learning, Reinforcement learning, Reinforcement learning, Others], Natural language processing [Context-aware computing, Computer vision]}, Application {Predictive maintenance and machinery inspection, Material movement, Production planning, Field services, Quality control, Cybersecurity, Industrial robots, Reclamation}, Digital Twin {Technology [Internet of Things (IOT), Blockchain, Artificial intelligence & machine learning, Artificial intelligence & machine learning, Big data analytics, 5G], Usage Type [Product digital twin, Process digital twin, System digital twin], Application [Product design & development, Performance monitoring, Predictive maintenance, Inventory management, Business optimization, Others]}, Automated Guided Vehicles (AGV) {Type [Tow vehicles, Unit load carriers, Pallet trucks, Assembly line vehicles, Forklift trucks, Others], Navigation Technology [Laser guidance, Magnetic guidance, Inductive guidance, Optical tape guidance, Vision guidance, Others]}, Machine Condition Monitoring {Monitoring Technique [Vibration monitoring, Embedded systems, Vibration analyzers and meters, Thermography, Oil analysis, Corrosion monitoring, Ultrasound emission, Motor current analysis], Offering [Hardware – Vibration sensors, Accelerometers, Tachometers, Infrared sensors, Spectrometers, Ultrasound detectors, Spectrum analyzers, Corrosion probes], Software [Data integration, Diagnostic reporting, Order tracking analysis, Parameter calculation], Deployment Type [On-premises deployment, Cloud deployment], Monitoring Process [Online condition monitoring, Portable condition monitoring]})IndustryManufacturing, Automotive, Energy, Medical, Semiconductor & Electronics, Food & Beverage, Oil & Gas, Aerospace, Metals & Mining, Chemicals, and OthersRequest Free Customization of this report:
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Internet of Things (IoT) Technology to Remain Indispensable for Industry 4.0
Internet of Things (IoT) remains the most crucial technology in global Industry 4.0 market growth owing to its role in interconnectivity and automation across different verticals. Advancements in connectivity technologies and rising use of automation in different industry verticals are also estimated to help this sub-segment gain an impressive market share. Surging demand for predictive maintenance will also boost the adoption of IoT technology in the long run.
Advanced robotic technologies are also slated to gain traction in the Industry 4.0 market. Growing acceptance of robots and high investments in advancements of robotic technologies are also slated to create new opportunities for providers of advanced robotics in the Industry 4.0 market. The low margin of error and the immense scope of automation are key benefits of robotics that help this sub-segment flourish.
Artificial intelligence (AI) will be another popular technology in the Industry 4.0 world going forward. Increasing demand for continuous monitoring, real-time analytics, and predictive maintenance are slated to help the demand for artificial intelligence in the future. The rising use of IoT devices will also boost the demand for cloud computing technology in the long run.
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Manufacturing Vertical to Spearhead Industry 4.0 Market Development
The manufacturing vertical is estimated to be at the forefront when it comes to Industry 4.0 adoption. The surge in use of robotics, advanced technologies, and smart manufacturing practices sets the tone for Industry 4.0 in this industry vertical. High emphasis on improving manufacturing efficiency, reducing downtime, and maximizing profits are all contributing to the high market share of this sub-segment.
The automotive industry is another vertical where Industry 4.0 market players could invest to get good returns. The high adoption of advanced robotics and other smart manufacturing technologies to maximize production allows this sub-segment to become a crucial one for Industry 4.0 providers. The aerospace and defense industry vertical also shows a lot of promise for Industry 4.0 companies going forward. Growing demand for advanced manufacturing techniques and technologies to create complex aerospace components is helping Industry 4.0 market growth via this segment.
The oil & gas industry is also estimated to embrace Industry 4.0 trend with open hands as they try to improve their operations and promote better resource utilization. High demand for predictive maintenance to reduce downtime and the growing adoption of digital oilfield solutions are estimated to bolster Industry 4.0 market development in the long run.
To sum it up, the application scope for Industry 4.0 is endless as automation and digitization pick up pace around the world. High investments in development of IoT and AI technologies will create better opportunities for Industry 4.0 companies in the future. The manufacturing industry will remain the top revenue generating sub-segment and more opportunities for aerospace, automotive, and oil & gas verticals will be seen over the coming years.
Related Report:
Digital Twin Market
Cyber Security Market
Artificial Intelligence (AI) Market
Internet Of Things (IoT) Market
Machine Learning Market
About Us:
SkyQuest is an IP focused Research and Investment Bank and Accelerator of Technology and assets. We provide access to technologies, markets and finance across sectors viz. Life Sciences, CleanTech, AgriTech, NanoTech and Information & Communication Technology.
We work closely with innovators, inventors, innovation seekers, entrepreneurs, companies and investors alike in leveraging external sources of R&D. Moreover, we help them in optimizing the economic potential of their intellectual assets. Our experiences with innovation management and commercialization has expanded our reach across North America, Europe, ASEAN and Asia Pacific.
Contact: Mr. Jagraj SinghSkyQuest Technology1 Apache Way,Westford,Massachusetts 01886USA (+1) 351-333-4748Email: [email protected] Our Website: https://www.skyquestt.com/
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Artificial Intelligence
Generative AI Cybersecurity Market worth $40.1 billion by 2030 – Exclusive Report by MarketsandMarkets™
CHICAGO, July 26, 2024 /PRNewswire/ — The Generative AI cybersecurity Market is anticipated to experience substantial expansion, ascending from a value of USD 7.1 billion in 2024 to a substantial worth of USD 40.1 billion by the year 2030, according to a new report by MarketsandMarkets™. This growth trajectory reflects a robust compound annual growth rate (CAGR) of 33.4% over the forecast period.
Browse in-depth TOC on “Generative AI cybersecurity Market”
350 – Tables 60 – Figures450 – Pages
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Scope of the Report
Report Metrics
Details
Market size available for years
2019–2030
Base year considered
2023
Forecast period
2024–2030
Forecast units
USD (Million)
Segments Covered
Offering, Generative AI-based Cybersecurity, Cybersecurity for Generative AI, Security Type, End-user, and Region
Geographies covered
North America, Europe, Asia Pacific, Middle East & Africa, and Latin America
Companies covered
Microsoft (US), IBM (US), Google (US), SentinelOne (US), AWS (US), NVIDIA (US), Cisco (US), CrowdStrike (US), Fortinet (US), Zscaler (US), Trend Micro (Japan), Palo Alto Networks (US), BlackBerry (Canada), Darktrace (UK), F5 (US), Okta (US), Sangfor (China), SecurityScorecard (US), Sophos (UK), Broadcom (US), Trellix (US), Veracode (US), LexisNexis (US), Abnormal Security (US), Adversa AI (Israel), Aquasec (US), BigID (US), Checkmarx (US), Cohesity (US), Credo AI (US), Cybereason (US), DeepKeep (Israel), Elastic NV (US), Flashpoint (US), Lakera (US), MOSTLY AI (Austria), Recorded Future (US), Secureframe (US), Skyflow (US), SlashNext (US), Snyk (US), Tenable (US), TrojAI (Canada), VirusTotal (Spain), XenonStack (UAE), and Zerofox (US).
This dramatic surge is being fueled by a number of causes. The primary growth driver is the enhancement of existing cybersecurity tools through generative AI algorithms by improving anomaly detection, automating threat hunting and penetration testing, and providing complex simulations for security testing purposes. These techniques enable various cyber-attack scenarios that can be simulated using the Generative Adversarial Networks (GANs), thus enabling the development of better preparedness and response strategies. On the other hand, it requires special cyber security tools to protect generative AI workloads against unique vulnerabilities such as adversarial attacks, model inversions and LLM poisoning. These tools include differential privacy and secure multi-party computation that are integrated into AI systems for training and deployment data protection purposes.
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Generative AI apps security segment will account for largest market share during the forecast period.
The cybersecurity landscape is rapidly changing for generative AI apps, which are already making their way into chatbots, content creation tools like word processors, and personalized recommendation systems. According to McAfee, 55% of these programs have had security breaches. This highlights the dire need for stronger protective measures from unauthorized access. Several generative AI applications that use adversarial techniques to force the desired reaction out of intelligent machines.
Therefore, there is a pressing demand in the number of developers who ensure that such machines are made more robust through techniques like adversarially trained models and resistant architectures. Finally, the usage of secure enclaves plus hardware-based security measures is growing off late, mainly aimed at safeguarding vulnerable AI computations from being tampered with. For instance, OpenAI has very strict security rules meant to protect GPT models thereby ensuring data integrity and user privacy.
By end-user, government & defense sector is poised to account for larger market share in 2024.
Government as well as defense industries are increasingly resorting to generative AI for cyber security purposes due to the urgency of protecting sensitive information and national security. According to a recent CSIS report, AI is being integrated into the cybersecurity framework of 43% of government agencies which resultantly improves their ability to identify and counter threats. As an example, the United States Department of Defense has started using artificial intelligence (AI) based security solutions backed by generative AI that can create fictitious cyber-attacks, thereby providing them with enhanced preparedness against advanced types of threats.
This technology also helps these sectors handle and analyze large volumes of data more effectively, giving valuable insights that will enable them prevent or mitigate cyber threats. This trend demonstrates an increasing reliance on generative AI in fortifying cyber security measures so as to ensure that critical infrastructure and sensitive data remain secure in today’s intricate digital landscape.
By region, North America to hold the largest share by market value in 2024.
In 2024, North America will be the leading region based on market share due to its excellent technology infrastructure, substantial investments in AI-enabled cybersecurity and the presence of key players. Major cyber security research universities and tech companies such as Google, AWS, CrowdStrike, SentinelOne and IBM are present in this area, pushing them on the forefront of potent risk management technologies and generative AI tools for threat detection. For example, IBM’s security platform powered by AI has improved detection rates for threats up by 40%, thus proving the relevance of AI technology to enhancing cybersecurity.
Moreover, legislative instruments such as Cybersecurity Information Sharing Act (CISA) are being put in place to promote advanced cybersecurity technologies. As internet attacks continue getting more complicated, North American enterprises prefer generative artificial intelligence (AI), so as to enhance their safety measures pertaining to personal data and digital infrastructure.
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Top Key Companies in Generative AI cybersecurity Market:
The major players in the generative AI cybersecurity market include Palo Alto Networks (US), AWS (US), CrowdStrike (US), SentinelOne (US), and Google (US), along with SMEs and startups such as MOSTLY AI (Austria), XenonStack (UAE), BigID (US), Abnormal Security (US), and Adversa AI (Israel).
Browse Adjacent Market: Artificial Intelligence (AI) Market Research Reports & Consulting
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Artificial Intelligence in Cybersecurity Market – Global Forecast to 2028
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Earlier this year, we made a formal transformation into one of America’s best management consulting firms as per a survey conducted by Forbes.
The B2B economy is witnessing the emergence of $25 trillion of new revenue streams that are substituting existing revenue streams in this decade alone. We work with clients on growth programs, helping them monetize this $25 trillion opportunity through our service lines – TAM Expansion, Go-to-Market (GTM) Strategy to Execution, Market Share Gain, Account Enablement, and Thought Leadership Marketing.
Built on the ‘GIVE Growth’ principle, we work with several Forbes Global 2000 B2B companies – helping them stay relevant in a disruptive ecosystem. Our insights and strategies are molded by our industry experts, cutting-edge AI-powered Market Intelligence Cloud, and years of research. The KnowledgeStore™ (our Market Intelligence Cloud) integrates our research, facilitates an analysis of interconnections through a set of applications, helping clients look at the entire ecosystem and understand the revenue shifts happening in their industry.
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